business-context-os

LLM wiki kit

First committed by walm00

Published in walm00/business-context-os. Publisher page

22 GitHub starsUpdated 2026-05-15

What it is

CLEAR Context OS is the maintenance layer your second brain never had: ownership boundaries enforced mechanically, staleness surfaced on a schedule, drift propagated across linked docs, a dispatcher that learns from your clicks. One source of truth per topic. Searchable. Task-aware.

— the description by walm00

AutoGineer overview, from the brain’s own files

CLEAR Context OS is a framework designed to solve the problem of silent context degradation in AI agents. By implementing a structured methodology called CLEAR (Contextual Ownership, Linking, Elimination, Alignment, Refinement), it provides a maintenance layer that manages knowledge through automated scheduling, ownership enforcement, and drift detection. It organizes information into specific zones—such as canonical data, wiki-based derivatives, and verbatim evidence—ensuring that agents always operate on the most accurate, source-of-truth-ranked information. The system includes a dispatcher for scheduled maintenance, a local dashboard for monitoring, and integration with Claude Code to facilitate onboarding and task-aware context retrieval.

How it works

Memory model: LLM wiki

AutoGineer overview, from the brain’s own files

The system organizes information into a folder hierarchy where the path itself acts as a trust signal for the LLM. It uses a dispatcher to run scheduled maintenance jobs that check for staleness, propagate updates across linked documents, and audit content health. New information is ingested through a routing process that places content into specific zones: canonical data for facts, wiki pages for operational knowledge, and collections for legal evidence. The system learns from user interactions to suggest fixes and uses frontmatter metadata to allow agents to filter and retrieve information efficiently without full-text scanning.

Folders
Folder	Role	Files
.claude	agent-config	193
.github	agent-config	6
docs	docs	68

The agent reads

docs/_bcos-framework/guides/folder-conventions.md evidence: CLAUDE.md
docs/_inbox/ evidence: README.md

The agent writes

docs/_inbox/ evidence: CLAUDE.md

Requirements

Works with: Claude Code, OpenCode

Set it up

This brain runs code automatically: 5 hooks (claude-code), 1 script. Review .claude/settings.json, install.sh before opening the folder in Claude Code. No step below turns a hook on for you.
- .claude/settings.json: bash "$CLAUDE_PROJECT_DIR/.claude/hooks/auto_save_session.sh"
- .claude/settings.json: bash "$CLAUDE_PROJECT_DIR/.claude/hooks/precompact_save.sh"
- .claude/settings.json: "$CLAUDE_PROJECT_DIR/.claude/bin/python3" "$CLAUDE_PROJECT_DIR/.claude/hooks/post_edit_frontmatter_check.py"
- .claude/settings.json: "$CLAUDE_PROJECT_DIR/.claude/bin/python3" "$CLAUDE_PROJECT_DIR/.claude/hooks/post_edit_frontmatter_check.py"
- .claude/settings.json: "$CLAUDE_PROJECT_DIR/.claude/bin/python3" "$CLAUDE_PROJECT_DIR/.claude/hooks/post_commit_context_check.py"
- install.sh: sh install.sh

Clone the repository at the commit AutoGineer scanned:

git clone https://github.com/walm00/business-context-os.git && cd business-context-os && git checkout 463568372f31f24fa6c01121c38f989845ca7c84

Claude Code reads CLAUDE.md from this folder automatically.
cd business-context-os && claude
AutoGineer scanned these files at commit 4635683.
First committed by walm00. Published in walm00/business-context-os. Licence: MIT License.

Usage

AutoGineer overview, from the brain’s own files

Automating the maintenance of project documentation and SOPs.
Providing AI agents with a reliable, freshness-aware knowledge base.
Managing ownership boundaries across large, multi-topic documentation sets.
Syncing and auditing context across linked documents to prevent drift.
Generating daily digests of system health and pending maintenance tasks.

“Install BCOS from https://github.com/walm00/business-context-os and walk me through onboarding.”: Claude clones the repository, sets up the environment, and guides the user through an interactive onboarding process to configure the context architecture.
“/context bundle market-report:write”: The agent retrieves a curated, freshness-aware package of context specifically relevant to writing a market report.
“Run the audit twice a week.”: The dispatcher updates the maintenance schedule to perform an audit of the knowledge base on a bi-weekly cadence.
“/wiki run https://stripe.com/docs/api”: The system fetches the URL, summarizes the content, and creates a cited wiki entry within the knowledge base.

Documentation by walm00

<h1 align="center">CLEAR Context OS</h1> Knowledge that maintains itself — so your AI doesn't act on what was true last month. <a href="#install">Install</a>  ·  <a href="#what-it-does">What it does</a>  ·  <a href="#the-wiki-zone">Wiki zone</a>  ·  <a href="#what-ships">What ships</a>  ·  <a href="docs/_bcos-framework/guides/getting-started.md">Getting Started</a> <img src="https://img.shields.io/badge/claude_code-ready-blueviolet" alt="Claude Code"> <img src="https://img.shields.io/badge/methodology-CLEAR-green" alt="CLEAR Methodology"> <img src="https://img.shields.io/badge/install-one_command-success" alt="One-command install"> <img src="https://img.shields.io/badge/skills-17-blue" alt="17 skills"> <img src="https://img.shields.io/badge/maintenance_jobs-12-orange" alt="12 maintenance jobs"> <img src="https://img.shields.io/badge/license-MIT-lightgrey" alt="MIT">

Your AI had perfect context — two weeks ago. Then your strategy shifted, three meetings redefined priorities, and the docs you wrote on Monday are wrong by Friday. CLEAR Context OS is the maintenance layer your second brain never had: ownership boundaries enforced mechanically, staleness surfaced on a schedule, drift propagated across linked docs, a dispatcher that learns from your clicks. One source of truth per topic. Searchable. Task-aware. Never silently stale.

Install

Easiest — let Claude do it. Open Claude Code in any directory and paste:

"Install BCOS from https://github.com/walm00/business-context-os and walk me through onboarding."

Claude clones the repo, picks the right install path for your platform (Windows/macOS/Linux), runs setup, and steps straight into onboarding. No prereq checks to debug — if something's missing, Claude resolves it interactively.

Or manually, two commands:

curl -fsSL https://raw.githubusercontent.com/walm00/business-context-os/main/install.sh -o /tmp/bcos-install.sh
bash /tmp/bcos-install.sh

(Requires bash, curl, and tar on PATH — fine on macOS/Linux and on Windows under WSL or Git Bash. Two steps instead of a single bash <(curl …) pipe so Claude Code's permission gate auto-approves both commands — you don't need to drop out to a terminal.)

Drop anything you already have — SOPs, brand docs, meeting notes, exports — into docs/_inbox/ (skip if you're starting fresh). Then open Claude Code in that repo and say:

"Launch BCOS onboarding."

That's the only prompt you need. Onboarding inspects your inbox, scans the rest of the repo, asks one Q&A round, and proposes the architecture for review. Works the same whether the repo is fresh or already full of context.

From zero to running

  INSTALL  →  DISCOVER  →  ALIGN  →  SCHEDULE  →  RUNNING

#	Step	What happens
1	Install	One bash line drops the framework into any repo
2	Discover	Claude scans your repo + any MCP you've connected (Drive, Notion, Slack, Gmail, your CRM — whatever's wired in) for existing context, plus anything you've dropped into `docs/_inbox/`
3	Align	One Q&A round — project type, key sources, ownership boundaries. Architecture drafted for your review
4	Schedule	Pick maintenance cadence in plain English: "audit twice a week", "dispatcher at 08:30", "deep daydream off"
5	Running	Daily digest. Local dashboard. `/context bundle <task>` ready. Context compounds from here — the system maintains itself.

Simple, guided, automatic. Claude walks you through each step — you review, you decide. Nothing deleted along the way — originals preserved or archived, never silently overwritten.

What it does

Stops context rot in three ways:

	What it does
Organize	Every doc declares what it owns. CLEAR boundaries prevent the same fact living in 5 places.
Maintain	Scheduled jobs check freshness, surface stale docs, propagate updates across linked content.
Use	`/context search` and `/context bundle <task>` give Claude curated, freshness-aware, source-of-truth-ranked context for the job at hand.

The folder tells the LLM what to trust. Claude reads the path before the content: docs/*.md = canonical, _planned/ = not yet real, _archive/ = history, _inbox/ = unprocessed, _collections/ = verbatim evidence, _wiki/ = explanatory. The hierarchy is the trust signal — fewer tokens spent re-deciding, no chance of treating an archived draft as today's truth.

docs/
├── *.md                  ← canonical data points (one source of truth per topic)
├── document-index.md     ← auto-generated TOC
├── current-state.md      ← what's true right now + what changed recently
├── table-of-context.md   ← high-level cluster map for orientation
├── _inbox/               ← drop zone — Claude triages on demand
├── _planned/             ← polished ideas, not yet real
├── _archive/             ← superseded — kept, not deleted
├── _collections/         ← verbatim evidence (invoices, contracts, transcripts)
│   └── <type>/_manifest.md   (each collection has a manifest)
├── _wiki/                ← derivative knowledge (how-tos, source summaries)
│   ├── pages/            ← user-authored explainers
│   ├── source-summary/   ← external captures with citation banners
│   ├── raw/              ← original artifacts (PDFs, HTML)
│   └── queue.md          ← URLs awaiting fetch
└── _bcos-framework/      ← framework docs — never user content
    ├── architecture/     ← 12 zone + system architecture docs
    ├── methodology/      ← 5 CLEAR + ownership + standards docs
    ├── patterns/         ← 8 project-type starting templates
    └── templates/        ← 15 frontmatter / schema / starter files

The wiki zone

Inspired by Karpathy's LLM Wiki approach — give the LLM a wiki of your knowledge, the way you'd brief a smart new hire.

Save anything to the wiki, from anywhere:

/wiki run https://stripe.com/docs/api          ← fetch a URL, summarize, cite
/wiki create from /Users/me/Downloads/spec.pdf ← extract a PDF, link to the binary
/wiki promote docs/_inbox/meeting-notes.md     ← turn an inbox capture into a wiki page

The wiki holds how-tos, runbooks, glossaries, source summaries, post-mortems, decision logs — derivative knowledge that explains and supports your canonical data points. Every page cites what it builds on. Stale pages surface automatically when their sources advance.

Wiki content is searchable alongside the rest of your context:

/context search "stripe billing"       ← cross-zone search, ranked by source-of-truth
/context bundle market-report:write    ← curated bundle for a specific task

The dashboard

A local cockpit at http://127.0.0.1:8091 that shows your system at a glance — no third-party services, no telemetry, no logins.

Image: BCOS dashboard cockpit — knowledge system status, things waiting on you, maintenance routine

python .claude/scripts/bcos-dashboard/run.py

Surface	What you see
Cockpit	One-line status (healthy / N waiting / heads-up). Per-job dot strip for every maintenance job (core BCOS + wiki zone).
Update	"Run full sync" button → `update.py` + CLAUDE.md drift review + auto-commit + push, with a live log drawer.
Schedules (`/settings/schedules`)	Per-job preset buttons (`daily`, `mon_wed_fri`, `weekly_mon`, `off`) + the global auto-commit toggle + auto-fix whitelist. Saves directly to `schedule-config.json`.
Run history (`/settings/runs`)	Last 20 dispatcher runs with filter chips (job / verdict / trigger).
File health (`/settings/files`)	Frontmatter / cross-reference / staleness findings with one-click fixes.

The dashboard is read-mostly: data flows from the dispatcher's diary, the schedule config, and the canonical context index. Writes (mark-done, schedule preset, auto-commit toggle, file fix) go through dedicated POST endpoints.

Requirements

Claude Code (desktop app, CLI, or web)
Python 3.8+ on PATH
bash (default macOS bash 3.2 is fine)

Updating

python .claude/scripts/update.py

Refreshes framework files only — skills, hooks, scripts, templates. Your docs/ and .private/ are never touched.

Maintenance

One scheduled task per repo. The dispatcher reads schedule-config.json, runs the jobs due today, writes one consolidated digest at docs/_inbox/daily-digest.md, and surfaces findings as one-click cards in the dashboard.

Image: BCOS maintenance schedule dispatcher — daily, weekly, monthly jobs flowing into the daily digest and dashboard cards

You can tune any of it in plain English:

"Run the audit twice a week." · "Move dispatcher to 08:30." · "Turn off deep daydream."

The system learns from your clicks. After three consistent uses of the same fix, the dashboard pre-selects it as a "✨ suggested" action — you accept or reject. Reversals trigger an automatic safety brake.

CLEAR — the methodology

Five principles, one rule each:

C — Contextual Ownership · one document owns each topic. No duplicates.
L — Linking · reference sources; don't copy them.
E — Elimination · consolidate; don't keep two versions.
A — Alignment · context that doesn't support decisions doesn't belong.
R — Refinement · structured maintenance, not ad-hoc fixes.

The whole framework is the mechanical implementation of these five rules.

What ships

Everything below installs as one repo drop-in. No third-party services, no logins, no telemetry — all state lives in your .claude/ and docs/ folders.

Layer	Count	Examples
Skills (chat-invokable via slash command)	17	`clear-planner` · `bcos-wiki` · `context-routing` · `context-audit` · `context-ingest` · `daydream` · `learning` · `schedule-tune` · `lessons-consolidate` · `ecosystem-manager`
Sub-agents (delegated bounded tasks)	3	`wiki-fetch` · `explore` · plus one optional
Scripts (mechanical Python)	46	`lifecycle_sweep` · `run_wiki_` (5) · `cmd_wiki_` (7) · `auto_fix_audit` · `bcos_inventory` · `digest_sidecar` · `record_resolution`
Hooks (auto-validation on edit)	4	post-edit frontmatter check · post-commit context check · pre-compact save · auto-save session
Maintenance jobs (scheduled, one dispatcher)	12	`index-health` · `audit-inbox` · `daydream-lessons` · `daydream-deep` · `architecture-review` · `auto-fix-audit` · `lifecycle-sweep` · `wiki-stale-propagation` · `wiki-source-refresh` · `wiki-graveyard` · `wiki-coverage-audit` · `wiki-canonical-drift`
Auto-fix IDs (silent dispatcher fixes)	12	`missing-last-updated` · `eof-newline` · `frontmatter-field-order` · `wiki-mark-queue-ingested` · `wiki-archive-expired-post-mortem`
Architecture docs	12	`wiki-zone.md` · `lifecycle-routing.md` · `typed-events.md` · `context-zones.md` · `content-routing.md` · `wiki-headless-scripts.md`
Methodology docs	5	CLEAR principles · context architecture · decision framework · document standards · ownership specification
Project patterns (starting templates by project type)	8	client-project · gtm · marketing · operational · product-development · product-service · internal-tool-app · internal-tool-automation
Templates (frontmatter, schema, starters)	15	data-point · cluster · current-state · table-of-context · wiki-schema · wiki-config · session-diary-starter

Every script and skill is documented at the source. Every job has a reference doc under .claude/skills/schedule-dispatcher/references/job-*.md. Every typed-event finding maps to a renderer in the dashboard cockpit. Adding a new check means dropping a cmd_*.py or run_*.py, registering it in one map, and the dashboard picks it up.

Contributing

Contributions welcome — open an issue or submit a PR targeting the dev branch. CI runs frontmatter, reference, and ecosystem-integration checks on every PR.

The fastest contribution path is lessons learned. As you use the system it captures insights; if you find one universal, contribute it back.

Origin

Built by Guntis Coders after two years of operating context systems in production. The CLEAR methodology emerged from a practical problem: AI context degrades silently, and no amount of one-time documentation prevents it. The solution required a system — ownership boundaries, automated maintenance, self-learning, and structured reflection.

Background: What is the Table of Contexts and why does it matter.

License

MIT

docs/_bcos-framework/architecture/maintenance-lifecycle.md

Maintenance Lifecycle -- How BCOS Stays Healthy

Context dies from neglect, drift, accumulation, ownership vacuums, and change blindness. The maintenance lifecycle is the defense system: layered checks at increasing time horizons that catch problems before they compound.

The Core Loop

graph LR
    A[Onboarding<br><i>day 1</i>] --> B[Daily use<br><i>context-ingest</i>]
    B --> C[Weekly<br><i>context-audit</i>]
    C --> D[Monthly<br><i>daydream</i>]
    D --> E[Quarterly<br><i>deep review</i>]
    E -->|"findings feed back<br>into daily work"| B

Each pass through the loop catches what the previous layer missed. The cycle repeats indefinitely -- there is no "done" state for maintenance.

Maintenance Phases

Phase selection depends on how fast context is changing, not how old the project is. A mature project entering a new market drops back to Building.

Building Phase (New Project)

First 1-2 months. Adding data points frequently. Architecture is still forming.

Task	Frequency	Implementation
Document Index rebuild	Daily	`python .claude/scripts/build_document_index.py`
Quick health check	Weekly	`context-audit` -- boundary violations, broken refs, naming drift
Lessons capture	Weekly	Capture what worked, what confused

Skip: Daydream (too early to reflect), deep audit (not enough content), quarterly review.

Active Phase (Growing)

3-6 months in. Editing more than creating. Architecture taking shape.

Task	Frequency	Implementation
Document Index rebuild	Weekly	`build_document_index.py`
Health check	Weekly	`context-audit` -- CLEAR audit + metadata validation
Daydream	Bi-weekly	`daydream` -- strategic reflection on gaps and relevance
Deep audit + lessons	Monthly	Full cluster audit, `lessons-consolidate`, repo re-scan

Steady Phase (Mature)

6+ months. Rare structural changes. Maintenance prevents silent drift.

Task	Frequency	Implementation
Document Index rebuild	Bi-weekly	`build_document_index.py`
Health check	Bi-weekly	`context-audit` -- lighter touch, staleness focus
Daydream	Monthly	`daydream` -- architecture still aligned with reality?
Deep audit + lessons	Quarterly	Full architecture review across all data points

Migration Phase (Consolidating)

Consolidating existing chaos into CLEAR structure. Burst activity for 1-3 weeks, then transition to Active.

Task	Frequency	Implementation
Document Index rebuild	Daily	Track progress as docs get formalized
Quick health check	Every 2-3 days	Catch contradictions between migrated and unmigrated docs
Progress review	Weekly	How many migrated? What remains?

Transition signal: When unmanaged docs reach zero, switch to Active rhythm.

What Triggers What

Automatic Triggers (Hooks)

Write-time validation catches issues at the moment of creation:

Edit/Write to docs/*.md fires frontmatter validation
Hook warns about missing or invalid metadata fields
Claude self-corrects before the file is committed

This is the fastest feedback loop -- problems caught in seconds, not days.

Scheduled Triggers (Dispatcher)

From v1.2 onward, BCOS installs a single scheduled task per repo — bcos-{project} — that runs daily and acts as a dispatcher. It reads .claude/quality/schedule-config.json to decide which maintenance jobs are due today, runs them in sequence, and produces one consolidated digest at docs/_inbox/daily-digest.md.

Eleven jobs, one dispatch:

Job	Default cadence	Purpose
`index-health`	daily	Rebuild index; structural scan; apply whitelisted auto-fixes
`daydream-lessons`	Mon	Weekly operational reflection + lessons capture
`daydream-deep`	Wed	Deeper structural reflection (splits, merges, retirements)
`audit-inbox`	Fri	Light CLEAR audit across all clusters + inbox aging + lessons triage
`auto-fix-audit`	Fri	Self-learning safety brake — surfaces high-reversal-rate rules
`lifecycle-sweep`	Fri	Classifier — routes outbound/decisions/research from active zone via `lifecycle:` field + body markers
`architecture-review`	1st	Full audit + ecosystem drift + health score + 3 priorities
`wiki-stale-propagation`	daily	Flag wiki pages whose `builds-on` sources moved on (cheap metadata-only check)
`wiki-source-refresh`	Mon	Two-tier source-summary freshness check + upstream HEAD probe
`wiki-graveyard`	1st	Monthly archive-candidate scan for stale / orphan / retired-type wiki pages
`wiki-coverage-audit`	quarterly	Cross-zone coverage scan — surfaces data points without wiki explainers

Every dispatcher run writes one diary line per job to .claude/hook_state/schedule-diary.jsonl — an append-only, gitignored history that the dispatcher reads to generate frequency-tuning suggestions (never auto-applies them).

Why one task, not five: user-global scheduled tasks collided when users ran BCOS across multiple repos, named checks were running daily despite "weekly" labels, and five separate morning reports created a UX mess. One task, one digest, one config file — changes happen in natural language through the schedule-tune skill.

Implementation: See docs/_bcos-framework/guides/scheduling.md for the full dispatcher model, config schema, and natural-language tuning examples.

Event-Driven Triggers

Business changes that should prompt immediate context review:

Event	Action	Affected Data Points
New product launch	Update via `context-ingest`	Value prop, product description, messaging, audience, competitive landscape
Competitor shift	Update competitive context	Competitive landscape, value prop, messaging, market context
Team restructure	Reassign ownership	All ownership assignments, cluster leads
New market entry	Create market-specific context	Market context, audience, competitive landscape, messaging
Rebrand	Cascade from brand identity outward	Brand identity, voice, messaging, visual identity, value prop

Implementation: See docs/_bcos-framework/guides/maintenance-guide.md for full trigger-to-data-point mapping.

Cascade Triggers

Maintenance tasks that spawn follow-up work:

graph LR
    A[daydream<br><i>finds stale docs</i>] -->|flags for| B[context-audit]
    B -->|finds contradictions| C[context-ingest<br><i>resolves</i>]
    C -->|finds no owner| D[New data point<br><i>recommended</i>]
    E[lessons-consolidate<br><i>finds gaps</i>] -->|suggests| F[New lessons<br><i>to capture</i>]

No maintenance task operates in isolation. Each one feeds the others.

The Daydream Cycle (Deep Dive)

Daydream is the strategic reflection layer. It asks: "Is our context architecture still aligned with reality?"

Implementation: .claude/skills/daydream/SKILL.md

How It Knows What Changed

Reads .claude/quality/last-daydream.txt for last run timestamp
Runs git log --since={date} scoped to docs/ only
Excludes framework directories: methodology/, guides/, templates/, architecture/
For each changed file, reads the actual git diff (not just the file list)
Checks for new or disappeared files via build_document_index.py --dry-run
Reads current-state.md and table-of-context.md for human signals

Four-Phase Process

Phase	Duration	Focus
1. What Changed	5 min	Git diffs, new/disappeared files, context layer signals
2. Reflect	10 min	Why did things change? Ripple effects? Missing updates? Folder zone health
3. Imagine	10 min	New team member test, new market test, 6-month vision, `_planned/` review
4. Capture	5 min	Promote `_planned/` to active, clean `_inbox/`, archive stale, update context layers

Short-Circuit

If nothing changed since last run, skip directly to Phase 3 (Imagine) for forward-looking reflection only. The git diff check makes this decision automatic.

Timestamp Tracking

After Phase 4 completes, the run date is written to .claude/quality/last-daydream.txt. The next daydream picks up exactly where this one left off. If the file does not exist (first run), daydream uses 2 weeks ago as baseline.

The Audit Cycle (Deep Dive)

Context-audit is the structural integrity layer. It checks whether documents follow CLEAR principles and flags violations by severity.

Implementation: .claude/skills/context-audit/SKILL.md

Severity Levels

Level	Meaning	Example	Action Timeline
CRITICAL	System integrity at risk	Missing YAML frontmatter entirely	Fix immediately
HIGH	Quality degradation	Missing required fields, duplication causing divergence	Fix this sprint
MEDIUM	Attention needed	Stale `last-updated` (>90 days active, >180 days planned)	Fix when in area
LOW	Informational	Missing optional fields, incomplete `_planned/` cross-refs	Nice to have

What Gets Checked

Metadata completeness -- 7 required fields per document:

name, type, cluster, version, status, created, last-updated

CLEAR compliance -- 5 audit categories:

Category	Checks For
Contextual Ownership	Multiple owners for same content, unclear responsibility, orphaned content
Linking	Duplicated information across data points, copy-paste, inconsistent cross-references
Elimination	Same content in multiple places, redundant data points, repeated hardcoded values
Alignment	Naming inconsistency, format differences, structure inconsistency
Refinement	Overly complex data points, vague language, missing maintenance metadata

Folder zone compliance:

docs/_planned/ docs older than 6 months: promote to active or archive
Active docs depending on _planned/ docs: flagged as forward-looking dependency
docs/_inbox/ files: skipped (raw material, no quality bar)
docs/_archive/ files: skipped or reported separately

Technical debt: TODO, FIXME, OUTDATED, DEPRECATED markers across all scoped files.

Priority Matrix

Every finding is scored: Priority = (Impact x Frequency) / (Effort x Risk), then placed into quadrants:

Quick Wins (high value, low effort) -- do first
Big Wins (high value, high effort) -- plan carefully
Low Priority (low value, low effort) -- do when convenient
Avoid (low value, high effort) -- not worth it

The Lessons System

Institutional knowledge compounds over time through the lessons system.

Implementation: .claude/skills/lessons-consolidate/SKILL.md

How Knowledge Compounds

Skills capture lessons in .claude/quality/ecosystem/lessons.json during normal work
Each lesson carries tags (CLEAR methodology tags + operational tags)
lessons-consolidate runs periodically to maintain collection health

Three Consolidation Modes

Mode	What It Does	Detects
Staleness check	Are lessons still relevant?	Referenced concepts that no longer exist
Overlap detection	Are multiple lessons saying the same thing?	Redundant lessons, contradictions
Gap analysis	What situations have no lessons?	Under-represented tags, uncovered topics

Consolidation Actions

Stale lessons: Archived (not deleted) -- moved to archived section
Overlapping lessons: Merged into single stronger lesson
Contradictions: Flagged for user resolution
Gaps: New lessons suggested for uncovered areas

Trigger Frequency

Monthly, or every 10-15 sessions, whichever comes first. If lessons.json feels cluttered, run sooner.

Scaling the Maintenance Rhythm

As context grows, increase maintenance frequency. Larger architectures have more surface area for drift.

Context Size	Index Rebuild	Audit	Daydream	Deep Review
< 20 docs	Weekly	Monthly	Monthly	Quarterly
20-50 docs	Weekly	Bi-weekly	Monthly	Quarterly
50-100 docs	Daily	Weekly	Bi-weekly	Monthly
100+ docs	Daily	Weekly	Weekly	Monthly

Adjustment signals:

3 consecutive checks find nothing: reduce frequency by half
Finding stale content regularly: increase frequency
Business changing faster than context: increase frequency
Scheduled tasks feel like noise: reduce frequency

The Self-Healing Pattern

BCOS layers four defenses at increasing time horizons. Each catches what the previous one missed.

Layer 1: Hooks (immediate)
  |  Catches: missing frontmatter, invalid metadata at write-time
  |
Layer 2: Scheduled audits (weekly)
  |  Catches: drift, boundary violations, broken cross-references
  |
Layer 3: Daydream (monthly)
  |  Catches: strategic misalignment, stale plans, missing connections
  |
Layer 4: Deep review (quarterly)
     Catches: architectural issues, ownership gaps, completeness problems

The pattern is deliberately redundant. A frontmatter issue caught by a hook never reaches the audit layer. A drift issue caught by the audit never reaches daydream. But if something slips through one layer, the next one picks it up.

The goal is not zero findings at any layer. The goal is no surprises -- issues are small and expected, not large and alarming.

Derived Artifacts vs. Authored Truth

A second, related principle: state files that mirror disk should be regenerated, not authored.

.claude/quality/ecosystem/state.json is an inventory — it records which skills, agents, and utilities exist. The disk is the source of truth (which directories have SKILL.md, which have AGENT.md, which have neither). The file just records what discovery found.

When a derived file is treated as authored truth and edited by hand, drift is inevitable. The file falls out of sync with disk the moment someone adds a directory and forgets to update the JSON. By the time the monthly architecture-review notices, the gap is large enough to be alarming.

The fix is to refresh the file from disk on a regular cadence — daily via index-health and at every framework update via update.py. The mechanism is the ecosystem-state-refresh auto-fix, governed by the same safety rules as every other whitelisted fix (deterministic, idempotent, no business-content change, reversible by git diff).

This principle generalizes: any registry, cache, or inventory file that mirrors a queryable source (disk, a database, an API) should follow the same pattern. The framework's lessons.json is the counter-example — it IS authored truth, and is therefore explicitly excluded from auto-refresh and only changed via the lessons-consolidate skill.

See lesson L-INIT-20260404-009: "Discovery scripts are the source of truth for what exists. State files record what discovery found, not the definition itself."

References

Resource	Path	Purpose
Scheduling guide	`docs/_bcos-framework/guides/scheduling.md`	Dispatcher model, config schema, natural-language tuning
Maintenance guide	`docs/_bcos-framework/guides/maintenance-guide.md`	User-facing maintenance rhythm and triggers
Schedule dispatcher	`.claude/skills/schedule-dispatcher/SKILL.md`	The single-task dispatcher that coordinates all jobs
Schedule tune	`.claude/skills/schedule-tune/SKILL.md`	Natural-language config editor
Daydream skill	`.claude/skills/daydream/SKILL.md`	4-phase reflection process
Context-audit skill	`.claude/skills/context-audit/SKILL.md`	CLEAR compliance checks and severity levels
Lessons-consolidate skill	`.claude/skills/lessons-consolidate/SKILL.md`	Knowledge compounding and cleanup
Document Index script	`.claude/scripts/build_document_index.py`	Automated index rebuild

278 files · 9 not served here

Advantages

Prevents context rot by surfacing stale information on a configurable schedule. evidence: README.md
Enforces ownership boundaries to ensure one source of truth per topic. evidence: README.md
Reduces token usage by providing a structured index that avoids redundant scanning. evidence: CLAUDE.md
Enables task-aware context retrieval through curated bundles. evidence: README.md

Limitations

Requires adherence to a specific folder structure and frontmatter schema to function correctly. evidence: README.md
Maintenance jobs and dispatcher functionality rely on Python and bash being available on the host system. evidence: README.md

Security

Risk level: Medium risk

This brain runs

Agent instructions that run or fetch something (170)

.claude/agents/wiki-fetch/AGENT.md: A 100k-token URL fetched into the main thread by `/wiki run` saturates the context window before a single page lands.
.claude/agents/wiki-fetch/AGENT.md: | Calling skill | Subcommand | Trigger | |---|---|---| | `bcos-wiki` | `run` Pass 1 | Each URL in the queue → one `wiki-fetch` invocation | | `bcos-wiki` | `refresh` full-tier | Source-summary past `stale_threshold_days` and HEAD signals changed | | `bcos-wiki` | `promote` (Path B) | S …[+132 chars] · uses the network
.claude/agents/wiki-fetch/AGENT.md: The cumulative budget guard ([`_wiki_budget.decide_dispatch_strategy`](../../scripts/_wiki_budget.py)) decides whether N sub-agents run in parallel or serial — `parallel` when projected cumulative tokens stay ≤ 80% of the main context limit;
.claude/agents/wiki-fetch/AGENT.md: queue an explicit retry tag for next run | | `error.kind: fetch-error` | 4xx/5xx from upstream | Surface to user;
.claude/agents/wiki-fetch/AGENT.md: `python .claude/scripts/test_wiki_fetch.py` — asserts this AGENT.md declares the documented input kinds and output fields, that the 4000-token cap is stated, that calling-skill docs reference both `wiki-fetch` and the Task tool, and that the result-schema validator + cumulative budget g …[+47 chars]
.claude/skills/bcos-wiki/SKILL.md: **`/wiki`** with subcommands: `init`, `init --defaults`, `run`, `queue`, `promote`, `create`, `review`, `archive`, `refresh`, `lint`, `remove`, `schema`, `search`
.claude/skills/bcos-wiki/SKILL.md: "Run the wiki refresh"
.claude/skills/bcos-wiki/SKILL.md: | | `run [<url>]` | implemented | P3 | Path A: batch (no arg) processes all `## Pending` queue items;
.claude/skills/bcos-wiki/SKILL.md: single (with URL) auto-queues + ingests | | `queue <url> [tags]` | implemented | P3 | Append URL to `## Pending` of `queue.md` without fetching | | `ingest` | shared protocol | P3 | Internal — called by `run`/`promote`/`create`;
.claude/skills/bcos-wiki/SKILL.md: optionally re-pull `builds-on` data points to verify | | `archive <slug>` | implemented | P3 | Soft-delete to `_wiki/.archive/` with dangling-reference scan | | `refresh <slug>` | implemented | P3 | Path A: re-fetch a `source-summary` page (refresh-must-rediscover applies, D-05 two-tie …[+470 chars]
.claude/skills/bcos-wiki/SKILL.md: `run` → `run.md`
.claude/skills/bcos-wiki/SKILL.md: Run `/wiki init` first."* and exit.
.claude/skills/bcos-wiki/SKILL.md: | Choice | Behavior | |---|---| | Init with defaults + proceed | Run `.claude/scripts/cmd_wiki_init.py` (or equivalent `ensure_wiki_zone.py` call).
.claude/skills/bcos-wiki/SKILL.md: Then resume the original subcommand (`create from`, `promote`, `run`, etc.) as if the Guard had passed.
.claude/skills/bcos-wiki/SKILL.md: | | Full interview + proceed | Read `init.md` and run the 6-question interactive scaffold.
.claude/skills/bcos-wiki/SKILL.md: The dispatched subcommand files (`create.md`, `promote.md`, `run.md`, `refresh.md`, `lint.md`, `archive.md`, `review.md`, `remove.md`, `schema.md`, `search.md`, `bundle.md`, `queue.md`) all reference *"the `.config.yml` Guard defined in `SKILL.md`"* — they inherit this AskUserQuestion p …[+46 chars]
.claude/skills/bcos-wiki/SKILL.md: The human reviews diffs and runs `git commit` / `git push` when ready. · uses the network
.claude/skills/bcos-wiki/SKILL.md: This applies to `run`, `refresh`, and `create` (when source content is large).
.claude/skills/bcos-wiki/SKILL.md: Users who want a binary in collections-as-evidence must run `/collections add` explicitly.
.claude/skills/bcos-wiki/SKILL.md: ├── run.md ← /wiki run [<url>]
.claude/skills/bcos-wiki/SKILL.md: ├── ingest.md ← shared ingest pipeline (called by run/promote/create/refresh)
.claude/skills/clear-planner/SKILL.md: Step 2: Run Discovery
.claude/skills/clear-planner/SKILL.md: { "step": 2, "name": "Run Discovery", "status": "in_progress" }
.claude/skills/clear-planner/SKILL.md: **Run all three discovery scripts:**
.claude/skills/clear-planner/SKILL.md: bash .claude/agents/agent-discovery/find_agents.sh
.claude/skills/clear-planner/SKILL.md: bash .claude/skills/skill-discovery/find_skills.sh
.claude/skills/clear-planner/SKILL.md: python .claude/scripts/find_lessons.py --tags "#{scenarioType}"
.claude/skills/clear-planner/SKILL.md: Run discovery scripts (Step 2 results)
.claude/skills/clear-planner/SKILL.md: | | ------------------- | ------------------------------------ | --------------------------------------------------------- | ------------------- | | Integration Audit | Detect stale references in ecosystem | `python .claude/scripts/analyze_integration.py --staged` + AI review | **YES …[+455 chars]
.claude/skills/clear-planner/SKILL.md: | Scenario | Key Requirement | | ----------------- | ------------------------------------------------------------------ | | **AGENTING** | Check for ecosystem overlaps + run integration audit before commit | | **DOCUMENTAT …[+76 chars]
.claude/skills/context-audit/SKILL.md: Run all five audit categories against the scoped files.
.claude/skills/context-audit/SKILL.md: python .claude/scripts/build_document_index.py
.claude/skills/context-ingest/SKILL.md: | Input shape | Dispatch to | Why | |-------------|-------------|-----| | HTTP/HTTPS URL (article, GitHub, YouTube) | `/wiki run <url>` (the `bcos-wiki` skill, Path A) | Wiki owns external-source ingest, banner citations, schema validation, refresh tier | | Path inside `docs/_inbox/` a …[+508 chars]
.claude/skills/context-ingest/SKILL.md: If the input is mixed (e.g. Slack export *and* a URL), do mine first, then handle the URL via `/wiki run` separately, then return to ingest for whatever's left.
.claude/skills/context-ingest/SKILL.md: Run `python .claude/scripts/build_document_index.py` after material changes
.claude/skills/context-ingest/SKILL.md: **→ Rebuild Document Index** — Always: `python .claude/scripts/build_document_index.py`
.claude/skills/context-ingest/SKILL.md: **→ context-audit** — If a new data point was created: "Want me to run a quick CLEAR audit on the new doc?"
.claude/skills/context-mine/SKILL.md: Recommend: "Run context-ingest to classify and route these items"
.claude/skills/context-onboarding/SKILL.md: | What you see | What you do | |---|---| | User shares a URL, pitch deck, or describes their business | Gather from those sources, ask 2-3 follow-ups if needed | | Repo already has docs/, README, markdown files with business content | Scan the repo, map what exists | | User drops files …[+394 chars] · uses the network
.claude/skills/context-onboarding/SKILL.md: Before anything else, run **once** per onboarding session to make sure the BCOS-managed instructions are present in `CLAUDE.md`.
.claude/skills/context-onboarding/SKILL.md: This catches the `git clone`-without-`install.sh` case: if `CLAUDE.md` exists but lacks the `` / `` markers, the framework section is missing or unstructured. · uses the network
.claude/skills/context-onboarding/SKILL.md: If `.claude/bcos-claude-reference.md` doesn't exist yet (fresh clone), point `--source` at the upstream template available in this repo's tree (the same file install.sh would have copied).
.claude/skills/context-onboarding/SKILL.md: **First-run routing principle:** onboarding is allowed to identify all BCOS zones, but it should only create active data points after the user approves the architecture.
.claude/skills/context-onboarding/SKILL.md: | Material | First-run handling | |---|---| | Canonical facts, current decisions, project/task/business reality | Draft active data points in `docs/*.md` | | Raw notes, unsorted snippets, uncertain material | Keep in `docs/_inbox/` until triaged | | Future ideas, plans, or maybes | Par …[+578 chars]
.claude/skills/context-onboarding/SKILL.md: Options: **Activate** (set all to active, run index + wake-up) / **Adjust** (tell me what to fix)
.claude/skills/context-onboarding/SKILL.md: Run `python .claude/scripts/build_document_index.py` to generate the Document Index with DOMAIN one-liners
.claude/skills/context-onboarding/SKILL.md: Run `python .claude/scripts/generate_wakeup_context.py` to generate the Wake-Up Context for instant session orientation
.claude/skills/context-onboarding/SKILL.md: The checklist ships with install at `docs/.onboarding-checklist.md`.
.claude/skills/context-onboarding/SKILL.md: Ensure the `.claude/hook_state/` directory exists (it usually does from install.sh — check and create if missing).
.claude/skills/context-onboarding/SKILL.md: the dispatcher will create it on first run.
.claude/skills/context-onboarding/SKILL.md: **Run the catalog drift guard:**
.claude/skills/context-onboarding/SKILL.md: python .claude/scripts/validate_permissions_catalog.py
.claude/skills/context-onboarding/SKILL.md: python .claude/scripts/update.py
.claude/skills/context-onboarding/SKILL.md: Re-run the validator to confirm clean.
.claude/skills/context-onboarding/SKILL.md: If the answer is "Yes, multi-repo" (or the user confirms after explanation), run:
.claude/skills/context-onboarding/SKILL.md: python .claude/scripts/install_global_permissions.py
.claude/skills/context-onboarding/SKILL.md: Question: "When should the morning dispatcher run?"
.claude/skills/context-onboarding/SKILL.md: Run the schedule-dispatcher skill to execute today's scheduled CLEAR maintenance. It will:
.claude/skills/context-onboarding/SKILL.md: 3. Execute each job in sequence, appending one diary entry per job
.claude/skills/context-onboarding/SKILL.md: The portfolio aggregator picks it up on the next dispatcher run.
.claude/skills/context-onboarding/SKILL.md: The dispatcher will run in the wrong directory and writes meant for this repo's `docs/_inbox/` will be blocked.
.claude/skills/context-onboarding/SKILL.md: If "Recreate", call `mcp__scheduled-tasks__delete_event` (or the equivalent delete tool) on the bad task, then re-run Step 6d.
.claude/skills/context-onboarding/SKILL.md: That's intentional — fresh setups should over-monitor for the first 1-2 weeks until the auto-tuner suggests reductions after green-run streaks.
.claude/skills/context-onboarding/SKILL.md: Let the user invoke the first run on their terms.
.claude/skills/context-onboarding/SKILL.md: A fresh install has nothing to migrate and should never see the word.
.claude/skills/core-discipline/SKILL.md: **Significant change** (restructure a cluster, create new skills) → use clear-planner, run the full workflow
.claude/skills/core-discipline/SKILL.md: | Task Type | Action | | ------------------------- | ---------------------- | | Questions, commands | Respond directly | | Single-file fixes | Just do it | | Small changes (1-3 files) | Think briefly, execute |
.claude/skills/core-discipline/SKILL.md: A scheduled dispatcher run finishes clean green with zero findings (one-line summary keeps the dashboard "Ready" status meaningful)
.claude/skills/core-discipline/SKILL.md: **Special case — wrapping scripts with built-in prompts** (like `update.py`'s `[y/N]` prompt): invoke the script with `--dry-run` first, parse the output, surface the summary via `AskUserQuestion`, then re-invoke with `--yes` based on the user's choice.
.claude/skills/daydream/SKILL.md: If the file doesn't exist, this is the first run — use 2 weeks ago as the baseline.
.claude/skills/daydream/SKILL.md: # Read last run timestamp (or default to 2 weeks ago)
.claude/skills/daydream/SKILL.md: cat .claude/quality/last-daydream.txt 2>/dev/null || echo "no previous run"
.claude/skills/daydream/SKILL.md: git log --since="{last_daydream_date}" --name-only --pretty=format:"%h %s (%ar)" -- docs/ ':!docs/_bcos-framework/methodology/' ':!docs/_bcos-framework/guides/' ':!docs/_bcos-framework/templates/'
.claude/skills/daydream/SKILL.md: Report "No document changes since last run" and skip to Phase 3 (Imagine) for forward-looking reflection only.
.claude/skills/daydream/SKILL.md: git diff {last_daydream_commit}..HEAD -- docs/path/to/changed-file.md
.claude/skills/daydream/SKILL.md: python .claude/scripts/build_document_index.py --dry-run
.claude/skills/daydream/SKILL.md: python .claude/scripts/generate_wakeup_context.py
.claude/skills/daydream/SKILL.md: **Step 5b: Run maintenance scripts**
.claude/skills/daydream/SKILL.md: Daydream is the natural time to run periodic maintenance:
.claude/skills/daydream/SKILL.md: python .claude/scripts/prune_sessions.py
.claude/skills/daydream/SKILL.md: python .claude/scripts/prune_diary.py
.claude/skills/daydream/SKILL.md: python .claude/scripts/generate_wakeup_context.py
.claude/skills/daydream/SKILL.md: python .claude/scripts/analyze_crossrefs.py
.claude/skills/daydream/SKILL.md: **Step 6: Record this run**
.claude/skills/daydream/SKILL.md: python .claude/scripts/record_daydream.py
.claude/skills/daydream/SKILL.md: **Document Index** — Run `python .claude/scripts/build_document_index.py` if files changed
.claude/skills/doc-lint/SKILL.md: If `.md`: Run markdown quality checks and cross-reference validation
.claude/skills/doc-lint/SKILL.md: If `.json`: Run JSON structure validation
.claude/skills/doc-lint/SKILL.md: Px_001: Run markdown quality check -> doc-lint (markdown category)
.claude/skills/doc-lint/SKILL.md: Px_002: Run example code validation -> doc-lint (cross_reference category)
.claude/skills/doc-lint/SKILL.md: Px_001: Run JSON structure validation -> doc-lint (json_structure category)
.claude/skills/doc-lint/SKILL.md: Px_002: Run markdown quality check -> doc-lint (markdown category)
.claude/skills/ecosystem-manager/SKILL.md: Run discovery to see what exists:
.claude/skills/ecosystem-manager/SKILL.md: bash .claude/agents/agent-discovery/find_agents.sh
.claude/skills/ecosystem-manager/SKILL.md: bash .claude/skills/skill-discovery/find_skills.sh
.claude/skills/ecosystem-manager/SKILL.md: Run it before committing.
.claude/skills/ecosystem-manager/SKILL.md: python .claude/scripts/analyze_integration.py --uncommitted
.claude/skills/ecosystem-manager/SKILL.md: Coverage gaps in install.sh, settings.json, state.json, .gitignore
.claude/skills/ecosystem-manager/SKILL.md: Add fix tasks to the plan and execute them before committing.
.claude/skills/ecosystem-manager/SKILL.md: [ ] **install.sh installs new files**
.claude/skills/ecosystem-manager/SKILL.md: Run after major development sessions or as part of monthly architecture review.
.claude/skills/ecosystem-manager/SKILL.md: Run `python .claude/scripts/wiki_schema.py list` to inspect page-types, lint-checks, and auto-fixes from `_wiki/.schema.yml` or the framework fallback.
.claude/skills/ecosystem-manager/SKILL.md: Run all 4 CI checks locally:
.claude/skills/ecosystem-manager/SKILL.md: python .github/scripts/validate_frontmatter.py # YAML metadata on all managed markdown
.claude/skills/ecosystem-manager/SKILL.md: python .github/scripts/validate_references.py # All registry paths resolve + state.json accuracy
.claude/skills/ecosystem-manager/SKILL.md: python .claude/scripts/analyze_integration.py --ci # Ecosystem wiring (install.sh, settings.json coverage)
.claude/skills/learning/SKILL.md: **Mechanism:** `python .claude/scripts/promote_resolutions.py` (the module's `__main__` calls `regenerate()`).
.claude/skills/learning/SKILL.md: Run the matching subcommand directly.
.claude/skills/lessons-consolidate/SKILL.md: python .claude/scripts/consolidate_lessons.py
.claude/skills/schedule-dispatcher/SKILL.md: Run `python .claude/scripts/update.py` first."
.claude/skills/schedule-dispatcher/SKILL.md: Report to the user: "schedule-config.json is malformed — fix before the dispatcher can run.
.claude/skills/schedule-dispatcher/SKILL.md: For each entry in `jobs`, decide if it should run today.
.claude/skills/schedule-dispatcher/SKILL.md: | `schedule` value | Runs when | |--------------------|----------------------------------------------------| | `"daily"` | Every day | | `"mon"`..`"sun"` | Only on that weekday …[+549 chars]
.claude/skills/schedule-dispatcher/SKILL.md: **For on-demand dispatch** (user said "run the audit-inbox job"): skip this step, run only the named job.
.claude/skills/schedule-dispatcher/SKILL.md: Build an ordered list of jobs to run.
.claude/skills/schedule-dispatcher/SKILL.md: python .claude/scripts/context_index.py --write
.claude/skills/schedule-dispatcher/SKILL.md: The cache TTL is 10 min (longer than a full dispatcher cycle), so all jobs in this run hit the same in-memory snapshot.
.claude/skills/schedule-dispatcher/SKILL.md: Last run timestamp per job?
.claude/skills/schedule-dispatcher/SKILL.md: Use the helper script — it creates `.claude/hook_state/` on first run and matches the allowlisted command prefix so it never prompts:
.claude/skills/schedule-dispatcher/SKILL.md: python .claude/scripts/append_diary.py '{"ts":"2026-04-15T09:04:12","job":"index-health","verdict":"green","findings_count":0,"auto_fixed":[],"actions_needed":[],"duration_s":4}'
.claude/skills/schedule-dispatcher/SKILL.md: **Fallback:** when `.bcos-umbrella.json` is absent (standalone BCOS install with no umbrella), preflight reduces to the `../` + absolute-path scans — no sibling-name list to check against.
.claude/skills/schedule-dispatcher/SKILL.md: After Step 4 completes (last job returned), verify that **every job listed in Step 2's run-list produced exactly one diary entry in this dispatcher tick**.
.claude/skills/schedule-dispatcher/SKILL.md: Read back the diary entries appended during this tick (use the dispatcher's in-memory record, or the tail of `.claude/hook_state/schedule-diary.jsonl` filtered to the current run's `ts` prefix if you're running on-demand).
.claude/skills/schedule-dispatcher/SKILL.md: **Added in schema 1.1.0.** Before applying auto-fixes (Step 5) or rendering the digest (Step 7), enrich each finding emitted in Step 4 with three computed fields and produce the run's headline string.
.claude/skills/schedule-dispatcher/SKILL.md: **Match against prior tick.** Scan diary entries from the **immediately-prior dispatcher tick** (the most-recent run before today, identified by the latest `ts` < today's run window).
.claude/skills/schedule-dispatcher/SKILL.md: | Run shape | Headline template | |---|---| | Green clean (0 findings, 0 framework) | "{Nth consecutive green run.}{recovery callout if any job verdict flipped error→green this tick.}" | | Green with frequency suggestions only | "All {N} jobs green.
.claude/skills/schedule-dispatcher/SKILL.md: And the run has a `headline` string ready for Step 7.
.claude/skills/schedule-dispatcher/SKILL.md: For each job run today, check recent diary:
.claude/skills/schedule-dispatcher/SKILL.md: **Last run was `error`** → suggest investigating, not frequency change
.claude/skills/schedule-dispatcher/SKILL.md: Both are overwritten each run.
.claude/skills/schedule-dispatcher/SKILL.md: Conditional sections render ONLY when their counts are non-zero — a green clean run is ~5 lines, an amber run with 5 findings is ~40 lines.
.claude/skills/schedule-dispatcher/SKILL.md: | 1 | `{emitted_by}` | `{primary_attr}` | {one-line meaning} | {`🔁 Nth run` if consecutive_runs ≥ 3, else blank} |
.claude/skills/schedule-dispatcher/SKILL.md: Run at {ISO timestamp} · `.claude/hook_state/schedule-diary.jsonl`
.claude/skills/schedule-dispatcher/SKILL.md: verdict emoji + finding count + inline status markers in Note column | | `💡 Suggestions` | `≥1` `frequency-suggestion` finding | Bullet list | | Footer | Always | Run timestamp, diary path, auto-commit status |
.claude/skills/schedule-dispatcher/SKILL.md: | Scenario | Verdict bar example | Top line | Action hint | |---|---|---|---| | Green clean | `**🟢 BCOS green** · 1 ran · 0 findings · 0 fixed · 4s` | `Headline string from Step 4c, e.g. "10th consecutive green run."` | `→ Nothing to act on.
.claude/skills/schedule-dispatcher/SKILL.md: Run `git rev-parse --abbrev-ref HEAD` to get the current branch.
.claude/skills/schedule-dispatcher/SKILL.md: This is the per-tick safety property: a stray hand-edit to a "generated" file on a day its owning job did not run still blocks auto-commit.
.claude/skills/schedule-dispatcher/SKILL.md: Globs are resolved against `git status --porcelain` paths (same surface the clean-tree rule already inspects).
.claude/skills/schedule-dispatcher/SKILL.md: **Emit the `job-missing-outputs-declaration` framework-finding only when** the job's run would have changed at least one path *outside* `GLOBAL_ALLOWED` (i.e. a path that *could* have been auto-committable had it been declared).
.claude/skills/schedule-dispatcher/SKILL.md: Run `git status --porcelain`.
.claude/skills/schedule-dispatcher/SKILL.md: `git commit -m "bcos: daily maintenance {YYYY-MM-DD}"` — no push, ever.
.claude/skills/schedule-dispatcher/SKILL.md: A BCOS install with no umbrella still writes the log — it just sits locally until somebody (or the dashboard) reads it.
.claude/skills/schedule-dispatcher/SKILL.md: The last thing the dispatcher does depends on whether the run produced anything that needs user judgement.
.claude/skills/schedule-dispatcher/SKILL.md: Otherwise — clean green run, zero findings, zero suggestions — output a short summary and stop.
.claude/skills/schedule-dispatcher/SKILL.md: **Why this rule:** if every run always asked a question, every scheduled run would show as "Awaiting input" in the dashboard even on clean days.
.claude/skills/schedule-dispatcher/SKILL.md: Or even shorter when the user is watching an on-demand run:
.claude/skills/schedule-dispatcher/SKILL.md: ("Do you want architecture review to run weekly?" is too abstract — `schedule-tune` handles that)
.claude/skills/schedule-dispatcher/SKILL.md: **Retry the failed job(s)** → re-run only the errored jobs (on-demand mode), then ask again with the new result
.claude/skills/schedule-dispatcher/SKILL.md: If the user says "run the {job-name} job now" or "run today's maintenance now":
.claude/skills/schedule-dispatcher/SKILL.md: Skip the schedule predicate — run only the named job(s)
.claude/skills/schedule-dispatcher/SKILL.md: ## On-demand run — {HH:MM} ({job-name})
.claude/skills/schedule-dispatcher/SKILL.md: If `daily-digest.md` does not yet exist (no scheduled run happened today), create it with a minimal header before appending the on-demand section.
.claude/skills/schedule-dispatcher/SKILL.md: DO append a diary entry per job with `"trigger":"on-demand"` so the run is tracked in history
.claude/skills/schedule-dispatcher/SKILL.md: Run another job
.claude/skills/schedule-dispatcher/SKILL.md: The morning scheduled run always OVERWRITES `daily-digest.md` fresh — so yesterday's on-demand sections are not preserved in the digest (diary retains them).
.claude/skills/schedule-dispatcher/SKILL.md: Every dispatcher run produces either a digest OR a user-facing error message.
.claude/skills/schedule-dispatcher/SKILL.md: `schedule-tune` — user-facing skill for changing config ("run audit twice a week")
.claude/skills/schedule-dispatcher/SKILL.md: If a run was wrong, add a corrective entry, don't mutate history.
.claude/skills/schedule-tune/SKILL.md: If you haven't set up BCOS scheduling yet, run `context-onboarding` Step 6.
.claude/skills/schedule-tune/SKILL.md: **Utterances:** *"run audit twice a week"*, *"change daydream to every 3 days"*, *"switch architecture review to quarterly"*, *"run index-health on weekdays only"*, *"audit on Tuesdays and Fridays"*
.claude/skills/schedule-tune/SKILL.md: **Utterances:** *"run the dispatcher at 08:30"*, *"move morning maintenance to 07:00"*
.claude/skills/schedule-tune/SKILL.md: Update the actual scheduled task's cron via `mcp__scheduled-tasks__update_scheduled_task` — that's what actually moves the run
.claude/skills/schedule-tune/SKILL.md: **Utterances:** *"what's my maintenance schedule?"*, *"when does audit run?"*, *"is architecture-review enabled?"*
.claude/skills/schedule-tune/SKILL.md: If the user proposes a cron that would run more than once per day, refuse: *"Dispatcher is designed to run once daily.
.claude/skills/schedule-tune/SKILL.md: | User says | Config edit | |----------------------------------------|----------------------------------------------------------------| | "run audit on Tuesday instead of Friday" | `jobs.audit-inbox.schedu …[+1012 chars]
.claude/skills/todo-utilities/SKILL.md: **Sequential Agent Invocation** — Tasks run one after another
CLAUDE.md: **Small changes (1-3 files)** — think briefly, execute.
CLAUDE.md: Auto-generated by `python .claude/scripts/generate_wakeup_context.py`.
CLAUDE.md: When unsure, run `context-ingest` and let it propose the route.
CLAUDE.md: **Post-work handoffs:** After integrating new content, offer to (a) rebuild the document index, (b) update related data points, (c) run an audit if architecture shifted.

Hooks (5)

.claude/settings.json (Stop): bash "$CLAUDE_PROJECT_DIR/.claude/hooks/auto_save_session.sh"
.claude/settings.json (PreCompact): bash "$CLAUDE_PROJECT_DIR/.claude/hooks/precompact_save.sh"
.claude/settings.json (PostToolUse): "$CLAUDE_PROJECT_DIR/.claude/bin/python3" "$CLAUDE_PROJECT_DIR/.claude/hooks/post_edit_frontmatter_check.py"
.claude/settings.json (PostToolUse): "$CLAUDE_PROJECT_DIR/.claude/bin/python3" "$CLAUDE_PROJECT_DIR/.claude/hooks/post_edit_frontmatter_check.py"
.claude/settings.json (PostToolUse): "$CLAUDE_PROJECT_DIR/.claude/bin/python3" "$CLAUDE_PROJECT_DIR/.claude/hooks/post_commit_context_check.py"

Install scripts (1)

install.sh: sh install.sh

Medium risk: runs-instruction-instruction-network (.claude/agents/wiki-fetch/AGENT.md:93)
Medium risk: runs-instruction-instruction-network (.claude/skills/bcos-wiki/SKILL.md:150)
Medium risk: runs-instruction-instruction-network (.claude/skills/context-onboarding/SKILL.md:33)
Medium risk: runs-instruction-instruction-network (.claude/skills/context-onboarding/SKILL.md:50)
Low risk: scripts-present (.claude/agents/agent-discovery/find_agents.sh)
Low risk: scripts-present (.claude/bin/python3)
Low risk: scripts-present (.claude/hooks/auto_save_session.sh)
Low risk: scripts-present (.claude/hooks/post_commit_context_check.py)
Low risk: scripts-present (.claude/hooks/post_edit_frontmatter_check.py)
Low risk: scripts-present (.claude/hooks/precompact_save.sh)
Low risk: scripts-present (.claude/scripts/analyze_crossrefs.py)
Low risk: scripts-present (.claude/scripts/analyze_integration.py)
Low risk: scripts-present (.claude/scripts/append_diary.py)
Low risk: scripts-present (.claude/scripts/audit_node_configs.py)
Low risk: scripts-present (.claude/scripts/auto_fix_audit.py)
Low risk: scripts-present (.claude/scripts/bcos_inventory.py)
Low risk: scripts-present (.claude/scripts/build_document_index.py)
Low risk: scripts-present (.claude/scripts/cmd_wiki_archive.py)
Low risk: scripts-present (.claude/scripts/cmd_wiki_init.py)
Low risk: scripts-present (.claude/scripts/cmd_wiki_lint.py)
Low risk: scripts-present (.claude/scripts/cmd_wiki_queue_add.py)
Low risk: scripts-present (.claude/scripts/cmd_wiki_remove.py)
Low risk: scripts-present (.claude/scripts/cmd_wiki_review.py)
Low risk: scripts-present (.claude/scripts/cmd_wiki_search.py)
Low risk: scripts-present (.claude/scripts/consolidate_lessons.py)
Low risk: scripts-present (.claude/scripts/context_bundle.py)
Low risk: scripts-present (.claude/scripts/context_index.py)
Low risk: scripts-present (.claude/scripts/context_search.py)
Low risk: scripts-present (.claude/scripts/digest_sidecar.py)
Low risk: scripts-present (.claude/scripts/find_lessons.py)
Low risk: scripts-present (.claude/scripts/generate_wakeup_context.py)
Low risk: scripts-present (.claude/scripts/install_global_permissions.py)
Low risk: scripts-present (.claude/scripts/lifecycle_sweep.py)
Low risk: scripts-present (.claude/scripts/load_task_profiles.py)
Low risk: scripts-present (.claude/scripts/load_zone_registry.py)
Low risk: scripts-present (.claude/scripts/promote_resolutions.py)
Low risk: scripts-present (.claude/scripts/prune_diary.py)
Low risk: scripts-present (.claude/scripts/prune_sessions.py)
Low risk: scripts-present (.claude/scripts/record_daydream.py)
Low risk: scripts-present (.claude/scripts/record_resolution.py)
Low risk: scripts-present (.claude/scripts/refresh_ecosystem_state.py)
Low risk: scripts-present (.claude/scripts/refresh_wiki_index.py)
Low risk: scripts-present (.claude/scripts/run_wiki_canonical_drift.py)
Low risk: scripts-present (.claude/scripts/run_wiki_coverage_audit.py)
Low risk: scripts-present (.claude/scripts/run_wiki_graveyard.py)
Low risk: scripts-present (.claude/scripts/run_wiki_source_refresh.py)
Low risk: scripts-present (.claude/scripts/run_wiki_stale_propagation.py)
Low risk: scripts-present (.claude/scripts/scan_docs_structure.py)
Low risk: scripts-present (.claude/scripts/set_profile.sh)
Low risk: scripts-present (.claude/scripts/update.py)