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Finding Deleted Feature Flags

PostHogOfficialPublished by PostHog

  • Skill
  • Research and analysis
  • Data and AI
  • MIT
  • Low risk
  • Has scripts

From the author

Find feature flags that were soft-deleted in the active project within a recent time window. Use when the user asks "what flags were deleted in the last N days", "show me recently deleted feature flags", "who deleted flag X", "audit recent flag deletions", or anything similar. Handles the non-obvious gotcha that system.feature_flags exposes the deleted boolean but does not expose a deletion timestamp — the actual deleted-at time lives in the per-flag activity log and must be cross-referenced.
— the description by PostHog

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a systematic approach to finding feature flags that have been soft-deleted within a specific timeframe. Because the primary feature flag system does not store deletion timestamps, this workflow uses a two-stage process: first, it queries the system for soft-deleted candidates, and second, it performs parallel lookups against the per-flag activity log to pinpoint the exact deletion time and the user responsible. It also includes a script to recover original flag keys from their tombstoned, suffixed versions.

What it does

  • Identifies soft-deleted feature flags in the active project.
  • Retrieves precise deletion timestamps and user attribution from activity logs.
  • Recovers original flag keys from tombstoned identifiers using a dedicated script.
  • Handles parallel data retrieval to optimize performance for multiple flag lookups.
  • Provides a structured report including flag ID, original key, deletion time, and the responsible user.

When to use it

  • When you need to audit which feature flags were deleted within a specific time window.
  • When you need to identify who deleted a particular feature flag.
  • When you are investigating recent changes to the project's feature flag configuration.
  • When you need to reconcile current flag states with historical deletions.

Advantages

  • Overcomes the lack of native deletion timestamps in the feature flag system.
  • Uses parallel processing to efficiently handle multiple activity log lookups.
  • Provides clear attribution for deletion events.
  • Automatically cleans up and recovers original flag keys for readable reporting.

Usage examples

“What feature flags were deleted in the last 7 days?”
The agent will query for soft-deleted flags, check their activity logs for the last week, and return a table of deleted flags with their original keys, deletion times, and the users who deleted them.
“Who deleted the flag example-banner?”
The agent will locate the flag, retrieve its activity history, and report the user who performed the deletion along with the timestamp.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/posthog/finding-deleted-feature-flags/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip finding-deleted-feature-flags.zip -d .agents/skills

Documentation by PostHog

Finding recently deleted feature flags

This skill produces a list of feature flags that were soft-deleted in the active project within a user-specified time window, along with who deleted each one and when.

When to use this skill

  • The user asks "what flags got deleted last week / in the last N days?"

  • The user wants an audit of recent flag deletions (who, when, what was removed)

  • The user wants to find when a specific flag was deleted, or by whom

  • Any "recently deleted feature flags" framing

Don't use this for active stale-flag cleanup — that's cleaning-up-stale-feature-flags. This skill is for flags that have already been removed.

The gotcha that makes this non-trivial

system.feature_flags exposes deleted as a boolean but does not expose deleted_at, updated_at, or last_modified_at. There's no way to filter soft-deleted flags by deletion time in a single SQL query — trying to use those columns will return Unable to resolve field.

The actual deletion timestamp lives in the per-flag activity log, reachable only via posthog:feature-flags-activity-retrieve (one call per flag id). There is no bulk activity endpoint.

So the workflow is two-stage: SQL to enumerate candidates, then parallel activity-log lookups to find each deletion event.

Workflow

1. Clarify the window if ambiguous

"Last week" is ambiguous — it can mean rolling 7 days from now, or the previous calendar week (Mon–Sun). If the user wasn't explicit, ask, or surface both interpretations in the final report.

Always compute the cutoff in UTC and keep the user's local interpretation in your head separately.

2. Enumerate soft-deleted flags via SQL

Query system.feature_flags for deleted = true in the active project, ordered by created_at DESC:

SELECT id, key, created_at
FROM system.feature_flags
WHERE team_id = <team_id> AND deleted = true
ORDER BY created_at DESC
LIMIT 100

Order by created_at DESC because deletions empirically cluster near creation — most flags get deleted within a few days of being created — so walking the most-recently-created candidates first finds recent deletions fastest. But this is a heuristic, not a guarantee: an older flag deleted recently won't be at the top of this list. Be explicit about that limitation when you report.

team_id defaults to the active project, but include it explicitly for clarity.

3. Fan out activity-log lookups in parallel

For each candidate id, call posthog:feature-flags-activity-retrieve with limit: 5, page: 1. Issue all calls in one message so they run concurrently — sequential calls are dramatically slower.

call feature-flags-activity-retrieve {"id": <flag_id>, "limit": 5, "page": 1}

Reasonable batch sizes:

  • "last 7 days" → top 20–25 candidates

  • "last 30 days" → top 50

  • "last 90 days" → walk the full ~100

If you sample fewer than the full set, say so in the report and offer to walk the rest as a follow-up.

4. Extract the deletion event from each response

In each response, find the entry where activity == "deleted". That entry's created_at is the actual deletion time, and user.email / user.first_name identify the deleter. These fields are reliable on every delete path.

For most flags there's exactly one delete event. If a flag has been deleted-and-restored multiple times, take the most recent activity: deleted event within the window.

5. Recover the original key and report

Feature flags are renamed to <original>:deleted:<flag_id> when soft-deleted while still referenced elsewhere (e.g. a stopped experiment) — the id-based suffix frees the original key for reuse. Don't try to recover the original from the activity log's own fields: detail.changes only carries the rename on UI/ORM deletes (and is often empty, or missing the key entry, on API/MCP/programmatic deletes), and detail.name just mirrors whatever the current key is — tombstoned or not.

Instead, strip the suffix deterministically with scripts/strip_deleted_suffix.py. Pass it the whole step 2 candidate list as JSON in one call — not one invocation per flag:

echo '[{"id": 1001, "key": "example-banner:deleted:1001"}]' | python3 scripts/strip_deleted_suffix.py
# prints the same array back (pretty-printed), each object gaining an "original_key" field:
# "original_key": "example-banner"

Filter the collected deletion events to those whose created_at falls inside the requested window. Present as a table, using each row's recovered original key (not the raw tombstoned form) for the "Key" column:

| Flag ID | Key | Deleted at (UTC) | Deleted by |

State your methodology in the report (how many candidates you walked vs. how many soft-deleted flags exist total), so the user knows what was and wasn't checked.

Watch-outs

  • Borderline cases: if a deletion is within ~1 hour of the window cutoff, surface it as borderline rather than silently dropping it.

  • Don't trust created_at as a proxy for deletion time: a flag created in 2024 can still have been deleted last week. The activity log is the only authority.

  • Renamed keys are normal: a flag with key foo:deleted:12345 was the flag originally keyed foo — see step 5 for how to recover it.

  • Walking all candidates is possible but slow: ~100 parallel activity-log calls is doable. Offer it as a follow-up rather than the default for short windows.

Example interaction

User: "what flags got deleted in the last week?"

  1. Clarify if needed, or note both interpretations: "rolling 7 days ending now (UTC), in the active project"

  2. Run the SQL enumeration to get up to 100 soft-deleted candidates ordered by created_at DESC

  3. Fan out activity-log lookups in parallel across the top ~25 candidates

  4. Extract activity: deleted entries; filter to those whose created_at >= now - 7 days

  5. Recover original keys with scripts/strip_deleted_suffix.py and report. The values below are illustrative, not real project data:

    Found 2 feature flags deleted in the last 7 days (rolling, ending 2026-08-14 09:30 UTC):
    
    | Flag ID | Key                     | Deleted at (UTC)     | Deleted by  |
    |---------|-------------------------|----------------------|-------------|
    | 1001    | example-banner          | 2026-08-13 15:12     | Jane D.     |
    | 1002    | example-checkout-test   | 2026-08-09 21:48     | John S.     |
    
    Methodology: walked the activity log for the 25 most-recently-created soft-deleted flags.
    The step 2 query hit its 100-row cap, so the project may have more soft-deleted flags than that.
    The other 75 returned candidates were created before late June 2026 and were not checked.
    Want me to walk the rest?
  • posthog:execute-sql: Used in step 2 to enumerate soft-deleted candidates against system.feature_flags

  • posthog:feature-flags-activity-retrieve: Used in step 3 to find the actual deletion event for each candidate

  • posthog:feature-flag-get-definition: Useful if the user then wants to inspect what the deleted flag looked like

Scripts

Files

Requirements and compatibility

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: Needs Python

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

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Attribution and licence

Published by
PostHog
Publisher
PostHog (Official)
Source
PostHog/skills · skills/omnibus/finding-deleted-feature-flags · commit a5d30e7
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download finding-deleted-feature-flags.zip