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 exploring-endpoint-execution-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/exploring-endpoint-execution-logs)<a href="https://agentmods.dev/skills/posthog/posthog-foss/exploring-endpoint-execution-logs"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/exploring-endpoint-execution-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/exploring-endpoint-execution-logs"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/exploring-endpoint-execution-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 55 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 | $0.00115 | $0.01520 |
| Opus 5 | $0.00057 | $0.00760 |
| Sonnet 5 | $0.00023 | $0.00304 |
| Haiku 4.5 | $0.00012 | $0.00152 |
Grade A, and why
exploring-endpoint-execution-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 7d 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:
- exploring-endpoint-execution-logs — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exploring endpoint execution logs
Every endpoint run emits one execution log entry to PostHog's log_entries store. This skill
reads those entries for a specific endpoint to answer "what happened when it ran?". It is the
log-level counterpart to diagnosing-endpoint-performance (which reasons about cache/materialisation
strategy from config and query_log).
When to use this skill
- "Why is my endpoint failing / erroring?"
- "Show me the logs / recent runs for endpoint X"
- "Did the last run hit cache? How many rows did it return?"
- "What happened the last time endpoint Y ran?"
If the question is "this endpoint is slow, what should I change?", use
diagnosing-endpoint-performance. If it's project-wide ("what can I clean up?"), use
auditing-endpoints.
What an execution log entry looks like
Each run produces exactly one entry. The level is INFO on success and ERROR on failure, and the
message carries the extra data as searchable key=value tokens:
Endpoint executed · path=materialized cache=hit duration_ms=142 rows=1024 version=3
Endpoint execution failed · path=inline error=ResolutionError version=3
Token meanings:
| Token | Values | Meaning |
|---|---|---|
path |
materialized / inline / ducklake / ducklake_fallback |
Which execution path ran |
cache |
hit / miss |
Whether the query result cache was used (omitted for ducklake) |
duration_ms |
integer | Wall-clock execution time |
rows |
integer | Number of result rows returned |
version |
integer | Which endpoint version ran |
error |
e.g. ResolutionError, HogVMException |
Error class / HogQL code name (failures only) |
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.
- 7d ago First seen · 127 lines · 115 tokens per session scan A 00bb5ae96f1e
exploring-endpoint-execution-logs is a skill published in the GitHub repository PostHog/posthog-foss (715 stars, last pushed today), licensed MIT. It adds 115 tokens to every session and 1,520 once invoked, about $0.0006 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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