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/posthog-foss --skill investigating-logsgit clone --depth 1 https://github.com/PostHog/posthog-fossWrote 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/posthog-foss/investigating-logs)<a href="https://agentmods.dev/skills/posthog/posthog-foss/investigating-logs"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/investigating-logs/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/posthog-foss/investigating-logs"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/investigating-logs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 36 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00137 | $0.01877 |
| Opus 5 | $0.00068 | $0.00938 |
| Sonnet 5 | $0.00027 | $0.00375 |
| Haiku 4.5 | $0.00014 | $0.00188 |
Grade A, and why
investigating-logs 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- investigating-logs — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigating logs
Investigation is a narrowing problem: summarize before you read.
One posthog:logs-patterns call compresses millions of lines into at most 200 templates,
and one posthog:logs-patterns-diff call answers "what is different about now vs. before" directly.
Raw rows (posthog:query-logs) are the last step of an investigation, never the first.
When to use this skill
- "Check the logs" / "is service X healthy?" / "did my deploy (or model bump, config change, migration) break anything?"
- "Why are errors up?" / "explain this spike" / incident triage — "what changed?"
- "What is this service logging?" — orienting in an unfamiliar or noisy stream.
- Finding the log evidence for a failure reported elsewhere (an alert, an error-tracking issue, a user complaint).
When not to use this skill
- Creating or tuning log alerts — that's
authoring-log-alerts. - Analytics over product events, persons, or insights — that's
querying-posthog-data. - HogQL exposes a
logstable viaposthog:execute-sql, but do not investigate through it: hand-written SQL over logs routinely hits read-byte caps and re-derives what the tools below do in one cheap call. Reserve SQL for the rare case of joining log-derived facts with non-log data.
Tools
| Tool | Job |
|---|---|
posthog:logs-services-create |
Top-25 services with log_count, error_count, error_rate, sparkline. Orientation. |
posthog:logs-patterns |
Mine one window's message templates, ordered by frequency. "What is this stream saying?" |
posthog:logs-patterns-diff |
Diff templates between two windows: new / rate-shifted / gone. "What changed?" |
posthog:logs-count / posthog:logs-count-ranges |
Scalar and time-bucketed counts for a filter. Localize volume before pulling rows. |
posthog:logs-sparkline-query |
Volume over time broken down by severity or service (the one bucketed view with a breakdown). |
posthog:logs-facet-values-create |
Distribution of severity/service (or a resource attribute) under a filter. |
posthog:logs-attributes-list / posthog:logs-attribute-values-list |
Discover attribute keys and values before building filters. |
posthog:query-logs |
Raw rows. Endpoint of every drill-down, entry point of none. |
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.
- 9d ago First seen · 123 lines · 137 tokens per session scan A 0efd1d73b0ca
investigating-logs is a skill published in the GitHub repository PostHog/posthog-foss (715 stars, last pushed today), licensed MIT. It adds 137 tokens to every session and 1,877 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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