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exploring-apm-traces

Investigates distributed application performance using PostHog APM (OpenTelemetry span) data via MCP. Use when the user asks about service traces, slow HTTP/database spans, error spans, error-rate trends or spikes, latency distributions, trace IDs, or span attributes — not AI observability traces or product logs. Uses posthog:query-apm-spans, posthog:apm-trace-get, posthog:apm-spans-sparkline, posthog:apm-services-list, posthog:apm-attributes-list, and posthog:apm-attribute-values-list.

75

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with executable examples and a strong tool inventory, and its progressive disclosure is well-structured with real reference and script files. Minor verbosity from guidance repeated across sections and some schema detail duplicated inline keep it just short of top marks.

Suggestions

Consolidate the 'always include _posthogUrl' guidance and the 'span attributes are in the payload' note into single canonical locations to remove repetition across Step 1, Constructing UI links, and Tips.

Move the duplicated enum/field detail in 'Common gotchas' and 'Trace JSON structure' to the existing references/spans-and-fields.md and link out instead of restating inline, tightening the SKILL.md overview.

Add an explicit validation checkpoint to the investigation workflows (e.g. 'confirm the returned span list is non-empty and the trace_id matches before aggregating') to lift workflow clarity to a 5.

DimensionReasoningScore

Conciseness

The body is largely lean and assumes Claude's competence (tool table, command snippets, field reference pointer), but several sections restate the same guidance across multiple places — e.g. the 'always include _posthogUrl' rule appears in Step 1, the 'Constructing UI links' section, and the Tips list, and the span-attributes-in-payload note repeats in three sections — which is mild padding that could be consolidated.

4 / 5

Actionability

Provides copy-paste-ready tool invocation blocks, concrete executable script commands with env-var usage, and specific filter JSON examples; every investigation pattern is backed by an exact command or tool call covering the common cases.

5 / 5

Workflow Clarity

The trace-debugging workflow is a clear two-step sequence with sub-steps, and investigation patterns are numbered with specific drill-downs, but there is no explicit validation/verification checkpoint (e.g. confirming a span set is non-empty before aggregating) for the read-heavy analytical operations; this is not a destructive/batch context so the hard cap does not apply, but explicit checkpoints would lift it to 5.

4 / 5

Progressive Disclosure

Structure is good: a concise overview, tool table, workflows, and clearly signaled one-level-deep references to references/spans-and-fields.md and the scripts/ directory, all of which exist as real files. It is not a 5 because the field/schema detail is duplicated inline (the Common gotchas and Trace JSON structure sections restate enum and field info that lives in the reference file) rather than purely pointing to it.

4 / 5

Total

17

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, trigger-rich, and explicit about both what it does and when to use it, with a strong disambiguation clause that sharply reduces conflict risk. It is a model example of a high-quality skill description.

DimensionReasoningScore

Specificity

Lists multiple concrete, distinct actions ('Investigates distributed application performance', 'service traces, slow HTTP/database spans, error spans, error-rate trends or spikes, latency distributions, trace IDs, or span attributes') and enumerates six specific MCP tools, giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Explicitly answers both 'what' (investigates distributed application performance using PostHog APM data via MCP) and 'when' ('Use when the user asks about service traces, slow HTTP/database spans, error spans, error-rate trends or spikes, latency distributions, trace IDs, or span attributes') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural user-facing phrasing ('service traces', 'slow HTTP/database spans', 'error spans', 'error-rate trends or spikes', 'latency distributions', 'trace IDs', 'span attributes') alongside the tool identifiers, covering the synonyms users would actually say.

5 / 5

Distinctiveness Conflict Risk

Names a clear niche (PostHog APM / OpenTelemetry traces via MCP) and explicitly excludes adjacent skills ('not AI observability traces or product logs'), minimizing conflict risk with related PostHog skills.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
PostHog/posthog
Reviewed

Table of Contents

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