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linkedin-analytics

Use when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis. Triggers on "why did my reach drop", "what's working on my LinkedIn", "analyze my posts", "do carousels do better for me", "should I test this", "LinkedIn analytics". Reads your own exported post data, reports medians and outlier bands, tests candidate patterns against a permutation null, and sizes a real experiment — refusing to conclude anything below 10 posts.

77

Quality

97%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

93%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 lean, highly actionable skill body: executable commands with exit-code contracts, a motivating rationale that justifies its statistical choices, clean one-level-deep bundle structure, and honest-reporting rules. The only gap is that failure-exit handling (exit 3) names the outcome but not what Claude should do next.

Suggestions

For exit code 3 in each step, add a short explicit action (e.g., 'on 3 unusable: tell the user what the export is missing and stop') so every failure exit has a feedback loop, not just exit 2.

State what to do when pattern_miner reports 'nothing survived' beyond reporting it honestly — e.g., name the default next step (proceed to experiment_planner only with a hypothesis from elsewhere, or stop).

DimensionReasoningScore

Conciseness

In ~90 lines the body covers three scripts' invocation, exit-code contracts, a rules checklist, and skill routing with no padding; even the opening anecdote ("carousels do 3x better for me, built on four posts") earns its place by motivating the refusal logic. No concept Claude already knows is re-explained, matching the 5-anchor (every token earns its place).

5 / 5

Actionability

Copy-paste bash commands are given for all three scripts with real flags, both input formats shown (posts.csv, posts.json), exit codes enumerated per step, and the CV derivation "1.4826 * MAD / median" spelled out. Specific and executable throughout, matching the 5-anchor.

5 / 5

Workflow Clarity

The four-step sequence is clear with exit-code checkpoints at each stage and explicit handling for the below-floor and "nothing survived" outcomes. However, exit 3 ("unusable" / "too long" / "refused") is labeled without an explicit next action, a minor validation gap that fits the 4-anchor (most checkpoints present, minor gaps) rather than the 5-anchor's full feedback loops.

4 / 5

Progressive Disclosure

The body is a genuine overview: three scripts described in a role table, two references and two assets each linked with a one-line purpose, all one level deep and all verified to exist in the bundle. Details are appropriately split out and navigation is easy, matching the 5-anchor.

5 / 5

Total

19

/

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 exemplary: explicit 'Use when' and 'Triggers on' guidance with six natural user phrasings, four-to-five concrete actions spanning the whole pipeline, and a refusal boundary that doubles as a differentiator. Voice is third person and every claim is explicit. No weaknesses found against any anchor below 5.

DimensionReasoningScore

Specificity

"Reads your own exported post data, reports medians and outlier bands, tests candidate patterns against a permutation null, and sizes a real experiment — refusing to conclude anything below 10 posts" lists multiple specific concrete actions covering the full analysis pipeline, plus an explicit refusal boundary. This matches the 5-anchor (comprehensive coverage); the 4-anchor would require a coverage gap, and none is apparent.

5 / 5

Completeness

Explicitly answers 'when' twice ("Use when someone wants to understand their own LinkedIn numbers" plus a separate "Triggers on" clause with concrete trigger phrases) and 'what' with a full action list. Exactly the 5-anchor pattern of concrete trigger phrases paired with concrete capabilities.

5 / 5

Trigger Term Quality

Six quoted natural phrases — "why did my reach drop", "what's working on my LinkedIn", "analyze my posts", "do carousels do better for me", "should I test this", "LinkedIn analytics" — cover diagnosis, comparison, and testing with synonym variation, all phrasings a user would actually say. Matches the 5-anchor; no commonly-said phrase class is missing.

5 / 5

Distinctiveness Conflict Risk

The niche is unmistakable — "their own LinkedIn numbers" on "your own exported post data" — and nearly all triggers are LinkedIn-flavored. Only "should I test this" is generic, and it sits among platform-specific phrases, so conflict risk is minimal (5-anchor), not merely 'minor overlap' (4-anchor).

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

alirezarezvani/claude-skills

Path

marketing/linkedin/skills/linkedin-analytics/SKILL.md

Reviewed

Table of Contents

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