Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add PostHog/skills --skill auditing-endpointsgit clone --depth 1 https://github.com/PostHog/skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/posthog/skills/auditing-endpoints)<a href="https://agentmods.dev/skills/posthog/skills/auditing-endpoints"><img src="https://agentmods.dev/badge/skills/posthog/skills/auditing-endpoints/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/posthog/skills/auditing-endpoints"><img src="https://agentmods.dev/badge/skills/posthog/skills/auditing-endpoints.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00096 | $0.02416 |
| Opus 5 | $0.00048 | $0.01208 |
| Sonnet 5 | $0.00019 | $0.00483 |
| Haiku 4.5 | $0.00010 | $0.00242 |
Grade A, and why
auditing-endpoints scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to auditing-endpoints — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auditing endpoints
This skill produces a project-wide audit of the Endpoints product. Use it when the user wants to find what to clean up — unused endpoints, failing materialisations, materialised versions that nobody calls any more. It does not modify anything; it reports.
The deeper investigation per endpoint is diagnosing-endpoint-performance. The audit's job is to
find candidates and hand off.
When to use this skill
- "Audit my endpoints" / "What endpoints can I clean up?"
- The user is taking over a project and wants to know what they've inherited
- A periodic review (monthly / quarterly) of endpoint sprawl
- The user is over a materialisation cost budget and wants to know what to disable
The dedicated tools give a fast endpoint-level view. For call frequency, recency, and cost over
time, query the query_log table with execute-sql (endpoint-level). Per-version recency comes
from endpoint-versions — each version carries its own last_executed_at.
Available tools
| Tool | What it's for |
|---|---|
execute-sql (HogQL) |
Primary read path. Query system.data_modeling_endpoints for metadata (name, is_active, current_version, derived_from_insight, last_executed_at) and query_log for endpoint-level usage (call counts, recency, duration, bytes) |
endpoint-materialization-status |
Per endpoint: is materialisation eligible, current status, last run, last error (not in the system tables — use this tool) |
endpoint-versions |
All versions for one endpoint, latest first, with each version's query, materialisation state, and last_executed_at |
endpoint-update |
Write path — disable (is_active: false) or unmaterialise (is_materialized: false) after the user confirms |
agent-feedback |
Tell the PostHog team what's missing or confusing in this flow so the product and skill improve |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 211 lines · 96 tokens per session scan A ad74830171cc
auditing-endpoints is a skill published in the GitHub repository PostHog/skills (60 stars, last pushed today), licensed MIT. It adds 96 tokens to every session and 2,416 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to auditing-endpoints, differing in 0 lines, and is treated as a copy.
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