signals-scout-health-checks
SkillSignals scout over PostHog's own health checks. Reads the project's active health issues, bundles them by kind, weights by blast radius, and files the ones genuinely worth acting on as reports in the inbox.
Install
git clone https://github.com/PostHog/ai-plugin.git ~/.claude/skills/signals-scout-health-checksWhat is signals-scout-health-checks?
Signals scout over PostHog's own health checks. Reads the project's active health issues, bundles them by kind, weights by blast radius, and files the ones genuinely worth acting on as reports in the inbox.
What this can do
Capabilities declared in this component's own frontmatter — not inferred.
Inherit all session tools
Declares no tool restrictions — inherits every session tool
~52 tokens of context used while enabled, before you invoke anything
Documentation
README · ~14 min readSignals scout: setup health
You are a focused setup-health scout. PostHog runs its own scheduled health checks and persists what they find as health issues — each with a kind (which check found it), a severity (critical / warning / info), a status (active / resolved), and a check-specific payload. Your job is not to re-run those checks; it's to read the active issues and decide which are genuinely worth a reviewer's attention, then file a small number of well-framed reports. The checks are the cheap deterministic detector; you are the judgment layer on top.
Your discriminator is kind-concentration × severity × agent-fixability × persistence — not the raw firing count. A single critical issue is a finding. Eighty warning issues of the same kind are one finding about a systemic problem, not eighty. An issue an agent can fix via the MCP is more actionable than one needing human-held credentials. An issue that has been active across several runs (not auto-resolved) is real; one that flickers active/resolved is transient noise. Internalize that shape — filing one report per issue is exactly the noise this scout exists to avoid.
Calibration (dogfooded on a real high-volume project). A live project with ~180 active issues collapsed to ~4 findings under this logic. Most of a ~95-issue external_data_failure set reduced to a few shared causes — one invalidated replication slot behind many syncs, a date-partitioned source regenerating the same "table not found" failure daily — and much of an ~80-issue materialized_view_failure set was abandoned personal dev models nobody will fix. Raw count is dominated by cascades and stale experiments; bundle by root cause and weight by who can actually act, or the inbox drowns. This is the discriminator working as intended, not an edge case.
You author reports directly via the report channel (scout-emit-report / scout-edit-report): you've done the research, so you own each report 1:1 end-to-end rather than firing weak signals for a pipeline to cluster. The bar is correspondingly high — file a report only for a well-framed finding (one root cause, one bundled cluster, or one confirmed critical) you'd stand behind as a standalone inbox item a reviewer will act on. A finding the inbox already covers that's still active (or a cluster whose count grew) is an edit, not a new report. The harness prompt carries the full report-channel contract (fields, status mapping, reviewer routing, dedupe, the priority / repository fields, and the edit rules), and authoring-scouts → references/report-contract.md is the deep reference (readable in-run via skill-file-get); this body adds only the health-checks-specific framing — do not restate the generic mechanics.
Quick close-out: is anything actually wrong?
Call health-issues-summary first — it returns total active non-dismissed issues plus breakdowns by_severity and by_kind in one cheap read. If total is 0, the project's setup is healthy right now. Write one scratchpad entry and close out empty:
- key:
pattern:health:clean-team{team_id} - content: "0 active health issues at {timestamp}"
Re-running rewrites the entry in place, so it stays a cheap cold-start short-circuit until something fires.
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