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chunk

Use CircleCI Chunk for AI-assisted CI/CD work through either the Chunk web UI or the chunk-cli. Trigger this skill when users ask to set up Chunk, troubleshoot or fix failing builds with Chunk, configure Chunk environments, schedule/proactively run Chunk tasks, or use chunk-cli commands such as init, validate, build-prompt, auth, sandbox, task, and skill install.

74

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

86%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 router skill: token-efficient, cleanly sequenced, with verified one-level-deep references and useful guardrails. The gaps are minor — no inline executable example or quick-start command, and the closing 'verification' step reports state rather than establishing a validate-and-retry feedback loop.

Suggestions

Add one or two quick-start commands inline (e.g., `chunk init` / `chunk validate` with a one-line note) so the most common CLI path is executable without loading the reference file.

Turn the closing verification step into a feedback loop: instruct to re-run validation or re-check org prerequisites on failure before reporting the next action.

State how to detect the correct path when a request is ambiguous (e.g., a failing build mentioned in chat with no terminal available), since the UI/CLI/mixed classification currently assumes the surface is already evident.

DimensionReasoningScore

Conciseness

The body is lean: no concept explanations, no padding, no restating what Claude already knows — the Overview is a single sentence and every other section (Workflow, Guardrails, Reference Map, Output Contract) carries only operational content. It matches the score-5 anchor ('every token earns its place'); nothing here reads as trimmable without losing instruction.

5 / 5

Actionability

The routing guidance is concrete — exact reference files to load per path ('load chunk-ui.md', 'load chunk-cli.md'), specific prechecks ('Confirm repository/project, branch, and whether GitHub integration is in place'), and explicit guardrails ('Never expose or log secret values'). It falls short of 5 because the body itself contains no executable command or example (e.g., a quick-start `chunk` invocation); all command detail is deferred to the references, so a common case can't be executed without an extra file load.

4 / 5

Workflow Clarity

The four steps are clearly sequenced (classify path → gather minimum context → execute via matching reference → close with verification), and step 4 is an explicit closing checkpoint ('State what was configured or run, what remains blocked, and the next safest command'). It is a 4 rather than 5 because the verification step is a reporting contract, not a validate-then-retry feedback loop — there is no instruction to re-check a failed validation or org prerequisite and recover, only 'verify those first' in the guardrails.

4 / 5

Progressive Disclosure

The SKILL.md is a pure overview that splits all detail into references/chunk-ui.md and references/chunk-cli.md — both verified to exist — each clearly signaled in both the Workflow and a dedicated Reference Map that describes what each file contains. References are exactly one level deep (the reference files link onward to nothing), matching the score-5 anchor.

5 / 5

Total

18

/

20

Passed

Description

96%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: it states what the skill covers (Chunk UI and CLI workflows), gives explicit 'Trigger this skill when...' guidance with concrete natural-language triggers, and enumerates real subcommands. The only residual risk is mild overlap on generic CI/CD phrases like 'fix failing builds' when Chunk is not named.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'set up Chunk, troubleshoot or fix failing builds with Chunk, configure Chunk environments, schedule/proactively run Chunk tasks' — and enumerates specific chunk-cli subcommands ('init, validate, build-prompt, auth, sandbox, task, and skill install'), giving comprehensive coverage across both UI and CLI surfaces. It exceeds the score-4 anchor ('several specific actions; minor gaps') because both the workflow verbs and the exact command families are named, leaving no obvious capability gap.

5 / 5

Completeness

It explicitly answers 'what' ('Use CircleCI Chunk for AI-assisted CI/CD work through either the Chunk web UI or the chunk-cli') and 'when' with a dedicated trigger clause ('Trigger this skill when users ask to...') listing concrete triggering requests. This mirrors the score-5 anchor example structure exactly; voice is third-person, so no specificity penalty applies.

5 / 5

Trigger Term Quality

Natural user phrasings are covered comprehensively with synonyms: 'set up', 'troubleshoot or fix failing builds', 'configure Chunk environments', 'schedule/proactively run Chunk tasks', plus the product names ('CircleCI Chunk', 'Chunk web UI', 'chunk-cli') and exact subcommand names a user would echo from an error or doc. It matches the anchor's bar of comprehensive natural-term coverage including variations; nothing a user would plausibly say when needing this skill is missing.

5 / 5

Distinctiveness Conflict Risk

The niche is clear — the proprietary product name 'Chunk'/'chunk-cli' plus unique subcommands ('build-prompt', 'skill install') make wrong-skill triggering unlikely. It sits at 4 rather than 5 because broadly applicable CI/CD phrases like 'troubleshoot or fix failing builds' and 'configure... environments' have minor overlap risk with general CI/CD or CircleCI-configuration skills when a user mentions build failures without naming Chunk.

4 / 5

Total

19

/

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
openai/plugins
Reviewed

Table of Contents

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