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ai-content-collaboration

How humans and AI compose in content workflows. Where AI legitimately participates, where humans must own, hybrid workflow patterns, voice ownership preservation, the AI slop problem, disclosure and transparency, team calibration, and the ethics of intellectually honest AI-assisted content production. Triggers on AI content workflow, AI-assisted writing, hybrid content production, AI in editorial, AI slop, AI disclosure, AI usage policy, AI content ethics, voice preservation with AI, team AI calibration. Also triggers when content feels generic despite quality tools, when team AI usage has drifted into inconsistency, or when a regulated or trust-sensitive context requires explicit AI policy.

70

Quality

86%

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

72%

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

The body is well-structured and actionable with excellent progressive disclosure (nine real one-level-deep reference files), but it carries editorial philosophizing that pushes conciseness below ideal, and its workflow checkpoints are largely implicit for batch/publish operations. Tightening the closing framing and adding explicit validate-and-proceed gates would lift the two level-2 dimensions.

Suggestions

Trim the editorial philosophizing in the closing and keystone sections ('AI in content workflows is neither magic nor menace...') to lift conciseness toward level 3 — the operational lists already carry the value.

Add explicit validation checkpoints for batch/publish operations, e.g. a fact-verification halt condition with a concrete re-check-and-proceed loop, so workflow_clarity reaches the explicit validate→fix→retry anchor.

Consider moving the 12-consideration framework's output spec into its own reference file to keep the overview lean while preserving the detailed workflow-document template.

DimensionReasoningScore

Conciseness

The body is mostly efficient domain guidance but padded in places with editorial philosophizing Claude does not strictly need ('AI in content workflows is neither magic nor menace...', 'Craft was always what made content worth reading') and repeated keystone restatements. This matches 'Mostly efficient but includes some unnecessary explanation or could be tightened' rather than level-3 leanness.

2 / 3

Actionability

It gives concrete executable guidance: 'Feed the AI 2 to 3 paragraphs of canonical brand voice', the 12-consideration framework, named disclosure language patterns, and pattern-by-pattern tradeoffs. For an instruction-only skill this is specific and actionable, matching 'specific examples; copy-paste ready'.

3 / 3

Workflow Clarity

The 12-consideration framework provides a clear audit sequence, but batch/risky operations (programmatic SEO generation, publish decisions) lack explicit validation checkpoints — fact verification is named as a halt condition but most feedback loops are implicit. This matches 'Steps listed but validation gaps' rather than the level-3 explicit-validate-and-retry anchor.

2 / 3

Progressive Disclosure

The body is a clear overview with well-signaled, one-level-deep references — each section ends in 'Detail in [references/...]' and a dedicated 'Reference files' section lists all nine files with descriptions; all referenced files exist in ./references. This matches 'Clear overview with well-signaled one-level-deep references'.

3 / 3

Total

10

/

12

Passed

Description

100%

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 strong across all dimensions: it enumerates concrete capability domains, packs in natural trigger terms users would actually say, and explicitly satisfies both the what and when clauses including situational triggers. It is a clear, distinctive niche unlikely to trigger the wrong skill.

DimensionReasoningScore

Specificity

Names multiple concrete capability domains rather than vague actions: 'Where AI legitimately participates, where humans must own, hybrid workflow patterns, voice ownership preservation, the AI slop problem, disclosure and transparency, team calibration'. This matches the 'Lists multiple specific concrete actions' anchor, not the level-2 'some actions' anchor which would name only a domain and a few actions.

3 / 3

Completeness

It explicitly answers both what ('How humans and AI compose in content workflows...') and when via 'Triggers on ...' plus a second 'Also triggers when content feels generic ...' situational clause. This clearly answers both what AND when with explicit triggers, exceeding the level-2 anchor where 'when is missing or only implied'.

3 / 3

Trigger Term Quality

Natural trigger terms a user would actually say are densely packed: 'AI content workflow, AI-assisted writing, hybrid content production, AI in editorial, AI slop, AI disclosure, AI usage policy, AI content ethics, voice preservation with AI, team AI calibration'. This is good coverage of natural terms rather than the level-2 'some relevant keywords but missing common variations'.

3 / 3

Distinctiveness Conflict Risk

It carves a clear niche — the workflow layer of AI-assisted content production — with distinct triggers unlikely to collide with adjacent single-skill catalog entries. This matches 'Clear niche with distinct triggers; unlikely to conflict' rather than level-2 overlap risk.

3 / 3

Total

12

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
rampstackco/claude-skills
Reviewed

Table of Contents

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