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arn-spark-report

This skill should be used when the user says "spark report", "report spark issue", "spark broke", "arn-spark-report", "greenfield issue", "report greenfield problem", "report spark problem", "diagnose spark", "spark doctor", "spark bug", "spark not working", or wants to report a problem with an Arness Spark workflow skill. Invokes the arn-spark-doctor agent to diagnose the issue, then files a GitHub issue on the Arness plugin repository. Do NOT use this for filing issues on the user's own project — use /arn-code-create-issue for that.

90

Quality

88%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Discovery

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.

This is an excellent skill description that thoroughly covers trigger terms, clearly explains what the skill does and when to use it, and explicitly disambiguates from a related skill. The extensive list of trigger phrases ensures reliable matching, and the negative boundary clause prevents misuse. The description uses appropriate third-person voice throughout.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: invokes the arn-spark-doctor agent to diagnose the issue, then files a GitHub issue on the Arness plugin repository. Also explicitly distinguishes what it does NOT do.

3 / 3

Completeness

Clearly answers both 'what' (invokes arn-spark-doctor to diagnose, then files a GitHub issue on the Arness plugin repo) and 'when' (extensive explicit trigger phrases listed at the start, plus a clarifying negative boundary). The 'Use when' equivalent is thoroughly addressed.

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms users would say: 'spark report', 'spark broke', 'spark not working', 'spark bug', 'diagnose spark', 'greenfield issue', and many more variations. These are highly natural phrases a user would actually type.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a clear niche (Arness Spark workflow issues specifically). The explicit negative boundary ('Do NOT use this for filing issues on the user's own project — use /arn-code-create-issue for that') directly addresses potential conflict with a similar skill, making disambiguation very clear.

3 / 3

Total

12

/

12

Passed

Implementation

77%

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

This is a well-structured, highly actionable skill with clear workflow sequencing, explicit consent gates, and comprehensive error handling with fallback paths. Its main weakness is moderate verbosity — the scripted user-facing dialogue, repeated fallback filename patterns, and the keyword routing table in Step 0 add tokens without proportional value. The referenced bundle files (issue-template.md, spark-knowledge-base.md) are not provided, making it impossible to fully validate progressive disclosure.

Suggestions

Condense the Step 1 scripted dialogue into a brief bullet list of what the process involves rather than a full quoted speech block.

Extract the repeated fallback filename pattern ('arness-spark-report-<YYYY-MM-DD>.md in the project root') into a single definition at the top and reference it throughout to reduce repetition.

DimensionReasoningScore

Conciseness

The skill is reasonably efficient but includes some unnecessary verbosity, such as the full scripted dialogue in Step 1 explaining the process to the user, and the detailed keyword lists in Step 0 that could be more compact. The error handling section repeats the fallback filename pattern multiple times.

2 / 3

Actionability

The skill provides concrete, executable commands (gh issue create, gh auth status, git remote get-url), specific file paths, exact variable references, and clear decision trees. The bash command in Step 6 is copy-paste ready, and prerequisite checks are specific and actionable.

3 / 3

Workflow Clarity

The workflow is clearly sequenced with numbered steps, explicit validation checkpoints (user consent before submission in Step 5), error recovery paths (retry without label, local file fallback), and a comprehensive error handling section covering multiple failure modes with specific remediation actions.

3 / 3

Progressive Disclosure

The skill references external files (spark-knowledge-base.md, issue-template.md) appropriately, but no bundle files were provided to verify these exist. The main SKILL.md is fairly long and the error handling section could potentially be extracted. The structure is reasonable but the content is somewhat monolithic for its length.

2 / 3

Total

10

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
AppsVortex/arness
Reviewed

Table of Contents

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