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collab-proof

Use when you want to understand what Claude contributed vs what you drove in a session. Triggers on: /collab-proof, session retrospective, ai contribution analysis, collaboration evidence, what did claude do.

56

Quality

63%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.gemini/skills/collab-proof/SKILL.md

The canonical home for this skill is collab-proof in alirezarezvani/claude-skills

SKILL.md
Quality
Evals
Security

Quality

Content

61%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 highly actionable, well-sequenced workflow with strong concrete code, but it is monolithic and long for a single SKILL.md, inlining content that belongs in separate reference files, which pulls down progressive disclosure and conciseness.

Suggestions

Move the inline Python token-collection script and the HTML template/CSS spec into reference files under references/ and link to them one level deep, improving progressive disclosure and conciseness.

Add an explicit validation checkpoint in Layer 03's HIGH path (e.g. verify DECISIONS.md entries are grounded before writing) to reach the top workflow_clarity anchor.

Trim the justification prose for special-case rules (High-Speed Execution Guard rationale, BUG_FIXING override) to one line each.

DimensionReasoningScore

Conciseness

The body is dense and actionable but lengthy, and includes some explanatory rationale prose (e.g. the High-Speed Execution Guard 'Rationale:' and BUG_FIXING special-rule justification) that could be trimmed.

3 / 5

Actionability

It provides concrete, mostly executable guidance — real git commands, a copy-paste Python token-collection script, and exact output formats — with only the HTML template left as an abbreviated placeholder.

4 / 5

Workflow Clarity

The three-layer pipeline is clearly sequenced with signal-level branching and explicit outputs, and the PreCompact feedback loop plus honesty rules add checkpoints, though Layer 03's HIGH path lacks an explicit validate-before-write gate.

4 / 5

Progressive Disclosure

It is a monolithic single-file skill with no bundle files and no external references; large reference-style material (the full HTML template, token script) is inlined rather than split into separate files, and structure is section-based but heavy.

2 / 5

Total

13

/

20

Passed

Description

66%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 clearly answers what and when with strong natural trigger terms, but is light on enumerating concrete capabilities, keeping specificity from the top anchor.

Suggestions

Add 1-2 concrete outputs the skill produces (e.g. 'generates DECISIONS.md entries, session-history markdown, and an HTML proof report') to raise specificity.

Consolidate the trigger list into a single explicit 'Use when...' clause to make the when-condition more concrete.

DimensionReasoningScore

Specificity

The description names the domain (understanding AI vs developer contribution) but concrete actions are minimal — it does not list specific operations like generating reports or appending to logs.

3 / 5

Completeness

Both the what ('understand what Claude contributed vs what you drove') and when ('Use when...') are present, but the 'when' relies on a listed trigger phrases rather than a single concrete situational clause.

4 / 5

Trigger Term Quality

It includes several natural trigger phrases (session retrospective, collaboration evidence, what did claude do) plus a slash-command trigger, though a couple of common synonyms are absent.

4 / 5

Distinctiveness Conflict Risk

The niche (AI collaboration evidence analysis) is fairly distinct with a clear trigger (/collab-proof) and specific phrasing, with only minor overlap risk against general retrospective tools.

4 / 5

Total

15

/

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
alirezarezvani/claude-skills
Reviewed

Table of Contents

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