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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.

72

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

Content

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 a clear multi-step workflow and thorough error handling. Its main weakness is moderate verbosity — particularly the scripted user-facing messages and the smart routing keyword lists — that could be tightened without losing clarity. The progressive disclosure is reasonable with references to external files, though the main file is on the longer side.

Suggestions

Trim the scripted user-facing messages in Steps 1 and 2 — Claude can compose appropriate explanations without verbatim scripts, and these consume significant tokens.

Consider condensing the smart routing keyword lists into a more compact format (e.g., a table or comma-separated inline list) to reduce token usage.

DimensionReasoningScore

Conciseness

The skill is reasonably efficient but includes some unnecessary verbosity — the full script for what to say to the user in Step 1 is overly prescriptive (Claude knows how to explain a process), and the smart routing keyword lists could be more compact. However, most content earns its place given the complexity of the workflow.

2 / 3

Actionability

The skill provides concrete, executable commands (gh issue create, gh auth status, git remote parsing), specific file paths, exact fallback behaviors, and clear tool specifications. Each step has actionable instructions rather than vague descriptions.

3 / 3

Workflow Clarity

The workflow is clearly sequenced (Steps 0-6) with explicit validation checkpoints: user consent before submission (Step 5), label existence check with retry (Step 6), prerequisite verification (Step 3), and comprehensive error handling with fallback paths for every failure mode.

3 / 3

Progressive Disclosure

The skill references external files (spark-knowledge-base.md, issue-template.md, ensure-config.md) appropriately, but no bundle files were provided to verify these exist. The main SKILL.md is quite long (~120 lines of substantive content) and the error handling section could potentially be extracted. The references are one-level deep and clearly signaled, which is good.

2 / 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.

This is an excellent skill description that covers all key dimensions well. It provides extensive trigger terms, clearly explains both what the skill does and when to use it, and explicitly disambiguates from a related skill. The only minor note is that the description is somewhat verbose, but the verbosity serves a functional purpose by enumerating trigger phrases comprehensively.

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' (diagnoses spark issues and files GitHub issues on the Arness plugin repo) and 'when' (explicit list of trigger phrases plus a general 'wants to report a problem with an Arness Spark workflow skill'). Also includes a negative boundary condition for disambiguation.

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms including many variations users would actually say: 'spark report', 'spark broke', 'spark not working', 'spark bug', 'diagnose spark', 'greenfield issue', etc. Covers both formal and informal phrasings.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a clear niche (Arness Spark workflow issues specifically). Explicitly disambiguates from /arn-code-create-issue for the user's own project, which directly reduces conflict risk with similar issue-filing skills.

3 / 3

Total

12

/

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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