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metrics

Builds your north star metric, a metric tree with owned input metrics and guardrails, and a review cadence, as a one-page metrics spec you can paste into a doc. Use it when you ask 'what should our north star be', 'which metric should this team goal on', 'our dashboard is a mess', 'how do we measure AI productivity', 'activation metric', 'OKR metrics', 'vanity metrics', or 'metrics review cadence'. Draws on 254 insights from 118 Lenny's Podcast guests incl. Sarah Tavel, Crystal Widjaja and Jessica Lachs.

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

82%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.

A well-structured, highly actionable playbook: a clear diagnose→route→run→deliver workflow, concrete guidance with real benchmarks throughout, and properly split one-level-deep references. The only deductions are minor: duplicated quote content inline, dense guest-name attribution that could be trimmed, and validation checkpoints attached to just one play.

DimensionReasoningScore

Conciseness

The body is dense with heuristics and assumes Claude's competence — no space is spent explaining what a metric or dashboard is, and nearly every line carries a specific instruction or benchmark (e.g., "client SDKs drop 20 to 30 percent of web events", "about 20 events, not a months-long documentation project"). Minor trims are possible: the 'Receipts' section duplicates six quotes already in references/quotes.md, and the per-guest attributions threaded through every sentence add tokens without changing the instruction.

4 / 5

Actionability

For an instruction-only skill the guidance is fully executable: a bounded diagnostic script ("ask only what you cannot infer, max 4"), a situation→play routing table, six numbered plays with concrete steps and real examples, a copy-paste-ready markdown one-pager template, and a 1/3/5-anchored grading rubric with a defined output format ("a score per criterion, the total out of 40, and the top 3 fixes"). This matches the top anchor for copy-paste-ready coverage of common cases.

5 / 5

Workflow Clarity

The sequence is clear and gated: read attached artifact first → ask max 4 diagnostic questions → route via the situation table → run the matched play → fill the one-pager → optionally grade existing work against the rubric. Checkpoints exist ("Done when: every roadmap item can state how it moves the metric", the grade rubric acting as a validation loop), but they are attached only to Play A; the other plays and the deliverable step have no explicit completion or verification check, matching level 4's 'most checkpoints present; minor validation gaps' rather than level 5.

4 / 5

Progressive Disclosure

The 'Go deeper' section signals exactly two one-level-deep references (references/frameworks.md, references/quotes.md) with a one-line description of each, both of which exist and contain no nested references, and the bulk framework detail is correctly kept in frameworks.md while the body stays a distilled playbook. Minor gaps keep it below level 5: the inline 'Receipts' quotes duplicate references/quotes.md, and the deliverable template plus grading table could arguably live in a reference file given the body's length.

4 / 5

Total

17

/

20

Passed

Description

88%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.

A strong description: third-person voice, explicit and comprehensive statement of what the skill builds, and an explicit 'Use it when' clause with eight natural trigger phrases. The only weakness is a few missing common synonyms (e.g., 'KPI', 'success metric') in the trigger list.

DimensionReasoningScore

Specificity

The description enumerates all the skill's concrete deliverables — "Builds your north star metric, a metric tree with owned input metrics and guardrails, and a review cadence, as a one-page metrics spec you can paste into a doc" — covering every major capability of the skill with no gaps. This matches the anchor for multiple specific concrete actions with comprehensive coverage, not the level 4 anchor of 'minor gaps in coverage'.

5 / 5

Completeness

It explicitly answers both questions: the 'what' ("Builds your north star metric, a metric tree with owned input metrics and guardrails, and a review cadence, as a one-page metrics spec") and the 'when' ("Use it when you ask 'what should our north star be'...") with concrete trigger phrases. This is a direct match for the top anchor; level 4's 'when could be more explicit' does not apply since the trigger list is explicit and enumerated.

5 / 5

Trigger Term Quality

Eight natural trigger phrases span both full questions users would say ('what should our north star be', 'our dashboard is a mess', 'how do we measure AI productivity') and short keyword nouns ('activation metric', 'OKR metrics', 'vanity metrics', 'metrics review cadence'), which is good coverage. It falls short of the level 5 'comprehensive' anchor because common synonyms like 'KPI' or 'success metric' are missing, but is well above level 3's 'missing common variations'.

4 / 5

Distinctiveness Conflict Risk

The niche is clear (metric selection and governance) and most triggers ('north star', 'vanity metrics', 'metrics review cadence') point uniquely here. Minor overlap risk remains with closely related product skills on broad terms like 'OKR metrics' and 'activation metric', matching the 'mostly distinct; minor overlap risk' anchor rather than level 5's 'minimal conflict risk'.

4 / 5

Total

18

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

menkesu/awesome-pm-skills

Path

skills/metrics/SKILL.md

Reviewed

Table of Contents

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