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ai-prompt-files

Create AI editor context files (.cursorrules, CLAUDE.md, GitHub Copilot instructions) that give AI coding tools deep knowledge of a project's API, conventions, and patterns. Use when someone wants their documentation project to work well with Cursor, Claude Code, GitHub Copilot, or other AI coding assistants. Also use when setting up developer experience for AI tools, creating project context files, or making a codebase more AI-assistant-friendly.

88

1.02x
Quality

85%

Does it follow best practices?

Impact

100%

1.02x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

78%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, actionable skill body with a clean five-step workflow and exemplary use of a single one-level-deep bundle reference for the detailed template. The main improvement opportunities are removing the duplicated day-1 quality test (stated identically in Step 2 and Quality Check) and adding an explicit self-validation step where Claude checks the generated file against the test questions before reporting.

Suggestions

De-duplicate the quality test: state the 'AI assistant that has only read this file should answer day-1 questions' criterion once (e.g., in Quality Check) and reference it from Step 2 instead of repeating it verbatim, and merge the overlapping test question lists.

Add an explicit validation step between Step 3 and Step 4: 'Validate: check the generated CLAUDE.md against each Quality Check test question; if any answer would be wrong or missing, add the missing information before proceeding.'

Make Step 1 info-gathering executable by adding the concrete commands to run (e.g., 'tree -L 3', 'cat package.json', 'ls src/content/') alongside the current descriptive list.

DimensionReasoningScore

Conciseness

The body is efficient overall — a compact tool table, terse steps, no concept explanations Claude already knows. It is held back from anchor 5 by redundancy: the day-1 test statement appears nearly verbatim in both Step 2 ('an AI assistant that has only read this file should accurately answer...') and the Quality Check section, and the test questions overlap between the two.

4 / 5

Actionability

Guidance is concrete: exact file paths ('{project_root}/CLAUDE.md', '.github/copilot-instructions.md'), an enumerated required-sections list, a filled-in example Project Overview, and a verification prompt ('ask "What is this project?"'). It stops short of anchor 5 because info-gathering in Step 1 is descriptive ('Read the following to gather context') rather than giving executable commands.

4 / 5

Workflow Clarity

The five steps are clearly sequenced and the Quality Check section supplies test questions as a checklist, with Step 5 including a verification instruction. It misses anchor 5 because validation is deferred to the user (testing in Cursor) rather than an explicit Claude-performed checkpoint between drafting and delivery; the sequence itself has no gaps, keeping it above anchor 3.

4 / 5

Progressive Disclosure

The body is a well-organized overview that points to a single, clearly signaled, one-level-deep reference ('Load assets/prompt-template.md'), which exists in the bundle and holds the detailed template content appropriately kept out of SKILL.md. This matches the anchor 5 pattern exactly.

5 / 5

Total

17

/

20

Passed

Description

87%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 that clearly states what the skill does and when to use it, with concrete file-name triggers and good natural-language coverage. Its only weakness is that it expresses one core action (create) rather than a fuller set of capabilities (e.g., updating or auditing existing context files, which the body actually covers).

DimensionReasoningScore

Specificity

The description names concrete artifacts ('.cursorrules, CLAUDE.md, GitHub Copilot instructions') and a clear outcome ('deep knowledge of a project's API, conventions, and patterns'), but centers on a single action verb ('Create'), leaving minor gaps in coverage versus the comprehensive multi-action anchor 5.

4 / 5

Completeness

It explicitly answers both what ('Create AI editor context files... that give AI coding tools deep knowledge of a project's API, conventions, and patterns') and when, with two concrete trigger clauses ('Use when someone wants their documentation project to work well with...'; 'Also use when setting up developer experience for AI tools...'), matching the anchor 5 example structure.

5 / 5

Trigger Term Quality

Strong natural keyword coverage including tool names (Cursor, Claude Code, GitHub Copilot), file names (.cursorrules, CLAUDE.md), and phrases like 'project context files' and 'AI-assistant-friendly'. A few natural variations are missing (Cline, Windsurf, .clinerules), so it falls just short of the comprehensive-synonyms anchor 5.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (AI editor context files) with distinct, hard-to-confuse triggers (.cursorrules, CLAUDE.md, copilot instructions); no other common skill would claim these triggers, matching anchor 5.

5 / 5

Total

18

/

20

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 2 missing

Warning

Total

15

/

16

Passed

Repository

kubical-ai/aeo-geo-optimization

Path

claude-code/skills/ai-prompt-files/SKILL.md

Reviewed

Table of Contents

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