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cc-skill-project-guidelines-example

Project Guidelines Skill (Example)

Quality

44%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./skills/cc-skill-project-guidelines-example/SKILL.md

The canonical home for this skill is cc-skill-project-guidelines-example in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

63%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.

The body is a well-sectioned, highly actionable project reference with concrete commands and code, but it is monolithic — all detail lives inline with no working bundle references — and a fair amount of it is generic boilerplate Claude could write unaided. The deploy workflow has pre-flight validation but no post-deploy verification or recovery loop.

Suggestions

Move the full code-pattern examples (ApiResponse, fetchApi, useApi, Claude integration) into references/ files (e.g. references/code-patterns.md, references/testing.md, references/deployment.md), keeping SKILL.md as a lean overview with well-signaled one-level-deep links.

Trim boilerplate Claude already knows — the stock fetch wrapper, generic useApi hook, and standard pytest fixture — down to only the project-specific conventions (the ApiResponse envelope shape, the /api prefix, the 80% coverage rule).

Add a post-deployment verification step and an error-recovery loop to the deployment workflow (e.g. check the Cloud Run service health endpoint, and roll back to the previous revision if it fails).

DimensionReasoningScore

Conciseness

The body delivers real project-specific value (tech stack, file tree, commands, critical rules) but pads it with generic boilerplate Claude already knows — a standard generic fetchApi wrapper, a textbook useApi hook, a boilerplate pytest fixture, and a stock Pydantic generic response — plus meta-fluff like 'This is an example of a project-specific skill.' This fits anchor 3 ('Mostly efficient but includes some unnecessary explanation or could be tightened') rather than 4, since several full code blocks could be trimmed to the project-specific parts.

3 / 5

Actionability

Guidance is concrete and mostly copy-paste ready: exact pytest/npm/gcloud commands, complete Claude tool-use example, env var listings, and a pre-deploy checklist. It falls short of anchor 5 only through minor gaps — useApi references ApiResponse<T> without importing it, and the pytest fixture uses the legacy AsyncClient(app=app) form that no longer runs as written — matching anchor 4 ('concrete code or commands with minor gaps').

4 / 5

Workflow Clarity

The deployment workflow has a clear sequence with a validation checkpoint before it (pre-deployment checklist: tests pass, build succeeds, no hardcoded secrets) plus explicit build/deploy commands, matching anchor 4 ('Clear sequence with most checkpoints present; minor validation gaps'). It is not a 5 because there is no post-deployment verification, error-recovery, or rollback feedback loop — only pre-flight checks.

4 / 5

Progressive Disclosure

Section headers are clear and the document is navigable, but everything is inlined in a single ~350-line SKILL.md — code patterns, testing details, and deployment docs that belong in separate reference files — and the 'Related Skills' pointers (coding-standards.md, backend-patterns.md, tdd-workflow/) reference files that are not part of the bundle. This matches anchor 3 ('Some structure... content that should be separate is inline') rather than 2, because the sections are well-organized and not a wall of text.

3 / 5

Total

14

/

20

Passed

Description

0%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 a bare title with no capabilities, no trigger terms, and no usage guidance. It would almost never be selected over competing skills and gives Claude no signal about when to load it.

Suggestions

Replace the title-as-description with concrete capabilities, e.g. 'Provides the Zenith project's architecture overview, file structure, code patterns (ApiResponse, fetchApi, useApi), testing requirements, and Cloud Run deployment workflow.'

Add an explicit trigger clause: 'Use when working on the Zenith codebase or when the user mentions this project, its API response format, or its deploy checklist.'

Include the natural keywords users would actually say — 'Zenith', 'Next.js', 'FastAPI', 'Supabase', 'deploy', 'project conventions' — so the skill surfaces for the right queries.

DimensionReasoningScore

Specificity

The description is only "Project Guidelines Skill (Example)" — it names a vague domain and lists zero concrete actions, matching the anchor 'Entirely vague; no concrete actions; pure abstract language' (cf. "Helps with documents"). It is not a 2 because even the domain-level action ('Processes PDF files') is absent; nothing describes what the skill does.

1 / 5

Completeness

Neither 'what' nor 'when' is present: there is no statement of what the skill does and no 'Use when...' clause or equivalent trigger guidance. Per the rubric guideline, a missing 'Use when' clause alone caps completeness at 3; here even the 'what' is just a title, matching anchor 1 ('Missing both what and when').

1 / 5

Trigger Term Quality

The only terms are 'Project', 'Guidelines', 'Skill', and 'Example' — no natural keywords a user would say when needing this skill (no 'codebase', 'architecture', 'conventions', project name, etc.). This matches anchor 1 ('No natural keywords; only technical jargon or entirely generic language') and is clearly below anchor 2's 'one or two generic keywords'.

1 / 5

Distinctiveness Conflict Risk

"Project Guidelines Skill (Example)" is entirely generic and would collide with any project-guidelines or coding-standards skill, matching anchor 1 ('Entirely generic; would conflict with virtually any skill'). Nothing pins it to a specific project, tech stack, or task.

1 / 5

Total

4

/

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

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

skills/cc-skill-project-guidelines-example/SKILL.md

Reviewed

Table of Contents

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