Discover Brand
AnthropicOfficialCreated by Tribe AIDistributed by Anthropic
- Skill
- Workflow
- Business and productivity
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill automates the process of locating, categorizing, and analyzing brand-related assets across various enterprise platforms including Notion, Confluence, Google Drive, Box, Microsoft 365, Figma, Gong, Granola, and Slack. It follows a structured workflow that orients the user, validates platform connectivity, performs a multi-source search, and generates a discovery report. The process is designed to identify authoritative brand guidelines, operational templates, and conversational patterns, while flagging potential conflicts or stale information for human review.
What it does
- Searches connected enterprise platforms for brand guidelines, style guides, and marketing assets.
- Categorizes and ranks discovered sources by trust level, recency, and relevance.
- Produces a structured discovery report highlighting key findings, conflicts, and open questions.
- Validates platform coverage and warns users if primary document storage is missing.
- Integrates with guideline generation skills to turn discovery results into formal brand documentation.
- Provides recommendations for resolving ambiguities or conflicting brand information.
When to use it
- When you need to audit existing brand content across the organization.
- When you are starting a new project and need to locate the official brand voice and style guides.
- When you suspect brand documentation is fragmented or inconsistent across different platforms.
- When you need to gather evidence to support the creation or update of a company style guide.
Advantages
- Reduces manual effort by automating searches across multiple disparate platforms.
- Ensures brand consistency by identifying conflicting or outdated documentation.
- Provides a clear, prioritized view of brand assets based on authoritative signals.
- Offers a transparent process with clear steps for user confirmation and review.
Usage examples
- “Find our style guide.”
- The agent will search connected platforms for documents labeled as style guides, rank them by recency and authority, and present a report on the most current version found.
- “Audit our brand content.”
- The agent will perform a broad discovery across all connected platforms, categorize findings into authoritative, operational, and conversational sources, and flag any conflicts or stale documents.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/anthropics/discover-brand/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip discover-brand.zip -d .agents/skills
Documentation by Tribe AI
Brand Discovery
Orchestrate autonomous discovery of brand materials across enterprise platforms. This skill coordinates the discover-brand agent to search connected platforms (Notion, Confluence, Google Drive, Box, Microsoft 365, Figma, Gong, Granola, Slack), triage sources, and produce a structured discovery report with open questions.
Discovery Workflow
0. Orient the User
Before starting, briefly explain what's about to happen so the user knows what to expect:
"Here's how brand discovery works:
Search — I'll search your connected platforms (Notion, Google Drive, Slack, etc.) for brand-related materials: style guides, pitch decks, templates, transcripts, and more.
Analyze — I'll categorize and rank what I find, pull the best sources, and produce a discovery report with what I found, any conflicts, and open questions.
Generate guidelines — Once you've reviewed the report, I can generate a structured brand voice guideline document from the results.
Save — Guidelines are saved to
.claude/brand-voice-guidelines.mdin your working folder once you approve them. Nothing is written until that step.
The search usually takes a few minutes depending on how many platforms are connected. Ready to get started?"
Wait for the user to confirm before proceeding. If they have questions about the process, answer them first.
1. Check Settings
Read .claude/brand-voice.local.md if it exists. Extract:
Company name
Which platforms are enabled (notion, confluence, google-drive, box, microsoft-365, figma, gong, granola, slack)
Search depth preference (standard or deep)
Max sources limit
Any known brand material locations listed under "Known Brand Materials"
If no settings file exists, proceed with all connected platforms and standard search depth.
2. Validate Platform Coverage
Before confirming scope, check which platforms are actually connected and classify them:
Document platforms (where brand guidelines, style guides, templates, and decks live):
Notion, Confluence, Google Drive, Box, Microsoft 365 (SharePoint/OneDrive)
Supplementary platforms (valuable for patterns, but not where brand docs are stored):
Slack, Gong, Granola, Figma
Apply these rules:
If zero document platforms are connected: Stop. Tell the user: "You don't have any document storage platforms connected (Google Drive, SharePoint, Notion, Confluence, or Box). Brand guidelines and style guides almost always live on one of these. Please connect at least one before running discovery. Gong/Granola/Slack transcripts are valuable supplements but unlikely to contain formal brand documents."
If no Google Drive AND no Microsoft 365 AND no Box: Warn (but proceed): "None of your primary file storage platforms (Google Drive, SharePoint, Box) are connected. Brand documents frequently live on these platforms. Discovery will proceed with [connected platforms], but results may have significant gaps. Consider connecting Google Drive or SharePoint."
If only one platform total is connected: Warn (but proceed): "Only [platform] is connected. Discovery works best with 2+ platforms for cross-source validation. Results from a single platform will have lower confidence scores."
3. Confirm Scope with User
Before launching discovery, confirm:
Which platforms to search (default: all connected)
Whether to include conversation transcripts (Gong, Granola) or just documents
Any known locations to prioritize
Keep this brief — one question, not a questionnaire.
4. Delegate to Discover-Brand Agent
Launch the discover-brand agent via the Task tool. Provide:
Company name (from settings or user input)
Enabled platforms
Search depth
Any known URLs or locations to check first
The agent executes the 4-phase discovery algorithm autonomously:
Broad Discovery — parallel searches across platforms
Source Triage — categorize and rank sources
Deep Fetch — retrieve and extract from top sources
Discovery Report — structured output with open questions
5. Present Discovery Report
When the agent returns, present the report to the user with a summary:
Total sources found and analyzed
Key brand elements discovered
Any conflicts between sources
Open questions requiring team input
6. Offer Next Steps
After presenting the report, offer:
Generate guidelines now — chain to
/brand-voice:generate-guidelinesusing discovery report as inputResolve open questions first — work through high-priority questions before generating
Save report — store the discovery report to Notion or as a local file
Expand search — search additional platforms or deeper if coverage is low
Open Questions
Open questions arise when the discovery agent encounters ambiguity it cannot resolve:
Conflicting documents (e.g., 2023 style guide vs. 2024 brand update)
Missing critical sections (e.g., no social media guidelines found)
Inconsistent terminology across platforms
Every open question includes an agent recommendation. Present questions as "confirm or override" — not dead ends.
Integration with Other Skills
Guideline Generation: The discovery report is returned by the discover-brand agent via the Task tool. Pass it directly to the guideline-generation skill as structured input, replacing the need for users to manually gather sources.
Brand Voice Enforcement: Once guidelines are generated from discovery, enforcement uses them automatically.
Error Handling
If zero platforms are connected, inform the user which platforms the plugin supports and how to connect them.
If all searches return empty results, flag the discovery as "low coverage" and suggest the user provide documents manually or check platform connections.
If a platform is connected but returns permission errors, note the gap and continue with other platforms.
Reference Files
For detailed discovery patterns and algorithms, consult:
references/search-strategies.md— Platform-specific search queries, query patterns by platform, and tips for maximizing discovery coveragereferences/source-ranking.md— Source category definitions, ranking algorithm weights, and triage decision criteria
Files
- ATTRIBUTION.mdAdded by AutoGineer1.1 KiB
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md6.7 KiB
- references/search-strategies.md9.0 KiB
- references/source-ranking.md9.0 KiB
references/source-ranking.md
Source Ranking Algorithm
How to categorize, rank, and prioritize discovered brand sources.
Source Categories
AUTHORITATIVE
Official, approved brand documentation. Highest trust level.
Signals:
Published style guides or brand books
C-suite or marketing leadership authored/approved
Lives in an official "Brand" folder or Confluence space
Has version numbers or approval dates
Referenced by other documents as "the brand guide"
Examples:
"Acme Corp Brand Guidelines v3.2.pdf"
"Official Style Guide" page in Confluence Marketing space
Brand book in Google Drive with company-wide sharing
Brand book in Box with company-wide sharing
Official Style Guide in SharePoint Marketing site
Trust weight: 1.0 (baseline)
OPERATIONAL
Brand applied in practice. Shows how guidelines manifest in real content.
Signals:
Templates actively used by teams
Sales playbooks with messaging guidance
Email sequences with established tone
Presentation templates with brand messaging
Examples:
"Cold Email Templates Q4 2024"
"Enterprise Sales Playbook"
"Customer Success Response Templates"
Pitch deck templates in Google Slides
Email templates in Outlook
Sales playbook on SharePoint
Trust weight: 0.8
CONVERSATIONAL
Implicit brand voice from actual communications.
Signals:
Sales call transcripts (especially successful ones)
Meeting notes with customer-facing language
Internal discussions about positioning
Slack threads discussing brand decisions
Examples:
Gong recordings of top performer calls
Meeting notes from brand strategy sessions
Customer success call transcripts
Slack #brand channel discussions about tone
Trust weight: 0.6 (valuable for patterns, not prescriptive)
CONTEXTUAL
Background information that informs brand but doesn't define it directly.
Signals:
Design files without explicit brand guidelines
Competitor analysis documents
Industry reports
Product documentation
Examples:
Figma component library (visual only)
"Competitive Landscape Q3 2024"
Product feature specifications
Trust weight: 0.3
STALE
Outdated content superseded by newer versions.
Signals:
Older version when a newer version exists
Pre-rebrand materials after a rebrand
Documents explicitly marked as deprecated
Content more than 2 years old without updates
Examples:
"Brand Guidelines v1.0" when v3.2 exists
"2022 Style Guide" when "2024 Brand Update" exists
Documents in an "Archive" or "Deprecated" folder
Trust weight: 0.1 (flag for review, do not rely on)
Ranking Algorithm
Apply these five ranking factors in order of priority:
1. Recency (Weight: 30%)
More recent sources are more likely to reflect current brand voice.
Score 1.0: Updated within last 6 months
Score 0.7: Updated within last year
Score 0.4: Updated within last 2 years
Score 0.1: Older than 2 years
When two sources conflict, the more recent one wins unless the older source is explicitly marked as the "official" guide.
Always prefer the most recent version of any document. When multiple sources cover the same topic, weight the newest one heavily. Flag any non-AUTHORITATIVE source older than 12 months in the discovery report.
Recency Cutoffs
In addition to soft recency scoring, apply hard cutoffs to prevent stale content from polluting discovery:
AUTHORITATIVE sources: No hard cutoff. Official brand guides remain valid regardless of age unless explicitly superseded by a newer version.
OPERATIONAL, CONVERSATIONAL, CONTEXTUAL sources: Exclude from deep fetch if older than 12 months, with one exception: if zero sources in a category fall within the 12-month window, include the single most recent source from that category and flag it as potentially stale.
STALE sources: Exclude entirely from deep fetch. Include in the discovery report for reference only.
These cutoffs apply at the deep-fetch stage (Phase 3). All sources are still collected during broad discovery (Phase 1) and triage (Phase 2) — the cutoffs filter what gets fully retrieved and analyzed.
2. Explicitness (Weight: 25%)
Sources that explicitly define brand voice outrank those that merely demonstrate it.
Score 1.0: Explicit brand instructions ("Our voice is...")
Score 0.7: Documented tone guidelines ("Emails should be...")
Score 0.4: Implicit patterns in templates or examples
Score 0.2: Inferred from conversational patterns
3. Authority (Weight: 20%)
Higher organizational authority indicates more trustworthy brand definitions.
Score 1.0: Official brand team or C-suite authored
Score 0.7: Marketing leadership authored
Score 0.4: Team leads or senior ICs
Score 0.2: Individual contributor or unknown author
4. Specificity (Weight: 15%)
Detailed, actionable guidance outranks vague principles.
Score 1.0: Specific rules with examples ("Use 'platform' not 'tool'")
Score 0.7: Detailed guidelines ("Tone should be warm but professional")
Score 0.4: General principles ("Be authentic")
Score 0.2: Abstract values only ("We believe in innovation")
5. Cross-Source Consistency (Weight: 10%)
Elements corroborated across multiple sources rank higher.
Score 1.0: Appears in 3+ independent sources
Score 0.7: Appears in 2 independent sources
Score 0.4: Appears in 1 source only
Score 0.1: Contradicted by another source
Composite Score Calculation
final_score = (recency × 0.30) + (explicitness × 0.25) + (authority × 0.20)
+ (specificity × 0.15) + (consistency × 0.10)Multiply by category trust weight:
ranked_score = final_score × category_trust_weightExample Scoring
Source: "Brand Voice Guidelines v3.2" (Confluence, updated 3 months ago)
Recency: 1.0 (3 months old)
Explicitness: 1.0 (explicit brand instructions)
Authority: 1.0 (marketing VP authored)
Specificity: 0.7 (good guidelines, some gaps)
Consistency: 0.7 (corroborated by email templates)
Category: AUTHORITATIVE (1.0)
Final: (1.0×0.30 + 1.0×0.25 + 1.0×0.20 + 0.7×0.15 + 0.7×0.10) × 1.0 = 0.925
Source: "Top Performer Call — Enterprise Close" (Gong, 2 months ago)
Recency: 1.0
Explicitness: 0.2 (implicit patterns only)
Authority: 0.4 (senior AE)
Specificity: 0.7 (specific phrases used)
Consistency: 0.4 (single source)
Category: CONVERSATIONAL (0.6)
Final: (1.0×0.30 + 0.2×0.25 + 0.4×0.20 + 0.7×0.15 + 0.4×0.10) × 0.6 = 0.345
Adaptive Scoring: No Authoritative Sources
When discovery finds zero AUTHORITATIVE sources, the scoring algorithm adapts to reflect that conversational and operational sources are the primary brand evidence.
Adjusted Trust Weights (No Authoritative Sources)
| Category | Default Weight | Adapted Weight | Rationale |
|---|---|---|---|
| AUTHORITATIVE | 1.0 | 1.0 | (n/a — none found) |
| OPERATIONAL | 0.8 | 0.9 | Templates become primary explicit evidence |
| CONVERSATIONAL | 0.6 | 0.85 | Transcripts are the best signal for how the brand actually communicates |
| CONTEXTUAL | 0.3 | 0.4 | Design and competitive context more valuable without formal docs |
| STALE | 0.1 | 0.2 | Even old docs matter more when nothing current exists |
Adjusted Explicitness Scoring (No Authoritative Sources)
When no authoritative sources exist, conversational patterns carry more prescriptive weight:
Score 0.2 → 0.5: "Inferred from conversational patterns" — these ARE the brand evidence now
Score 0.4 → 0.6: "Implicit patterns in templates or examples"
Other explicitness scores unchanged
Example: Transcript Scoring With Adaptation
Source: "Top Performer Call — Enterprise Close" (Gong, 2 months ago)
Recency: 1.0
Explicitness: 0.5 (adapted from 0.2 — patterns are primary evidence)
Authority: 0.4 (senior AE)
Specificity: 0.7 (specific phrases used)
Consistency: 0.4 (single source)
Category: CONVERSATIONAL (0.85 adapted)
Adapted score: (1.0×0.30 + 0.5×0.25 + 0.4×0.20 + 0.7×0.15 + 0.4×0.10) × 0.85 = 0.552
This puts the transcript well above the 0.5 deep-fetch threshold, ensuring conversational sources meaningfully contribute to guideline generation.
When to Apply
Apply adaptive scoring when:
Phase 2 triage produces zero AUTHORITATIVE sources
Flag in the discovery report: "No formal brand guidelines found — scoring adapted to weight conversational and operational sources higher"
Triage Decision Criteria
Include in Deep Fetch (Top 5-15 sources)
Ranked score > 0.5
All AUTHORITATIVE sources regardless of score
At least one source per category if available (this overrides the score threshold)
At least one source per platform if available
Flag for Review
Sources with conflicting information
STALE sources that may still be referenced by teams
Sources with high specificity but low authority
Exclude
Ranked score < 0.1
Clearly irrelevant results (e.g., "brand" used in product name, not brand guidelines)
Duplicate content already captured from another platform
Requirements and compatibility
Written for: Claude Code, Claude apps
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Names Claude Code tools
Security
No issues found by our static scan· No issues found
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Attribution and licence
- Created by
- Tribe AI
- Publisher
- Anthropic (Official)
- Distributed by
- Anthropic
- Source
- anthropics/knowledge-work-plugins · partner-built/brand-voice/skills/discover-brand · commit e050c2e
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from partner-built/brand-voice/LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Tribe AI or Anthropic.
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