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-mcp-tool-qualitygit 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-mcp-tool-quality)<a href="https://agentmods.dev/skills/posthog/posthog-foss/exploring-mcp-tool-quality"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/exploring-mcp-tool-quality/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-mcp-tool-quality"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/exploring-mcp-tool-quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00094 | $0.02019 |
| Opus 5 | $0.00047 | $0.01009 |
| Sonnet 5 | $0.00019 | $0.00404 |
| Haiku 4.5 | $0.00009 | $0.00202 |
Grade A, and why
exploring-mcp-tool-quality 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 3d 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-mcp-tool-quality — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exploring MCP tool quality
Any MCP server instrumented with PostHog's MCP analytics SDK emits a
$mcp_tool_call event on the shared events table every time an agent invokes a
tool. There is no dedicated ClickHouse table — every field lives as a
$mcp_* property on events, and every tool-quality metric (error rate, latency
percentiles, reach) is an aggregation over this one event. This is the data
behind the MCP analytics dashboard and tool-quality screens.
Governed metric first
For any MCP failure-rate headline, call posthog:metric-list before a typed tool or SQL recipe and look for mcp_tool_call_fail_pct. If it is approved and not drifted, run it with posthog:data-catalog-metric-run and use that result as the canonical headline. When the user also asks which tools drive failures, run the headline first, then use the workflows below for the breakdown and label that breakdown noncanonical. If no governed metric matches, state that the catalog has no match and label the derived rate noncanonical.
For a single tool, prefer the typed tools — posthog:query-mcp-tool-stats (calls,
errors, p50/p95, users, sessions, intents), posthog:query-mcp-tool-failures (top error
messages by harness), and posthog:query-mcp-tool-daily-stats (day-by-day trend). Each
takes a toolName + dateRange, runs the same query runner as the tool-detail
UI, and is gated behind the mcp-analytics flag — no hand-written SQL needed.
HogQL via posthog:execute-sql is the path for cross-tool questions — the
"which tool errors most" ranking below has no typed tool, so rank with SQL, then
drill into the worst tool with posthog:query-mcp-tool-stats and
posthog:query-mcp-tool-failures. The full
property schema and the established query recipes live in the shared MCP data
reference:
products/posthog_ai/skills/querying-posthog-data/references/models-mcp.md.
That reference is the single source of truth for the $mcp_* schema and the
effective-tool-name idiom used below — this skill inlines only the noncanonical
"which tool errors most" breakdown for convenience; pull the matrix, latency, and
harness recipes from the reference rather than re-deriving them. Read it before
writing queries.
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.
- 3d ago Changed · +4 lines 2f8a4a6b8b97
- 9d ago First seen · 155 lines · 94 tokens per session scan A ec6b89f5da7e
exploring-mcp-tool-quality is a skill published in the GitHub repository PostHog/posthog-foss (715 stars, last pushed today), licensed MIT. It adds 94 tokens to every session and 2,019 once invoked, about $0.0005 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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