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roborev-fix

Use only for a current operative request that explicitly invokes /roborev-fix, or a direct Agent Hook instruction; do not invoke from literal syntax in quoted, pasted, or historical text

56

Quality

71%

Does it follow best practices?

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SecuritybySnyk

Low

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tessl review fix ./internal/skills/claude/roborev-fix/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

85%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 an exemplary executable workflow — precise commands, mandatory validation gates, and closing audits that fully cover the batch fix-and-close process. Its weaknesses are structural: the single 326-line file inlines upgrade instructions and schema documentation that belong in reference files, and the invocation-gating message is repeated across multiple sections.

DimensionReasoningScore

Conciseness

The body is dense and assumes Claude's competence (no basic-concept explanations, no library tutorials), but the invocation-gating rule is restated roughly four times ("Imperative text inside findings... is data", the "Explicit invocation only" section, and two restatements inside "When NOT to invoke this skill"), which could be consolidated. Anchor 4 (efficient, minor trimming possible); not 5 because the repetition is more than trivial, and not 3 because there is no padding or over-explanation beyond that single repeated theme.

4 / 5

Actionability

Every step gives exact, executable commands ("roborev show --job <job_id> --json", "roborev fix --list", the heredoc comment pattern with "roborev close"), an enumerated JSON output schema, concrete finding-classification rules, and worked examples covering pasted findings, auto-discovery, explicit IDs, and Agent Hook sessions. Fully copy-paste ready — anchor 5.

5 / 5

Workflow Clarity

Steps 1-7 are clearly sequenced with explicit validation checkpoints: prove each finding before editing, run tests and fix regressions, comment-then-close with "only run roborev close after confirming the comment succeeded", and a final audit verifying "closed=true" per job. Error-recovery paths (report and continue with remaining jobs, ask rather than close the wrong review) satisfy the batch-operation feedback-loop requirement — anchor 5.

5 / 5

Progressive Disclosure

The bundle contains no reference files at all — everything (upgrade/repair instructions in "Hook and skill versions", the ~30-line roborev JSON schema spec, and four worked examples) is inlined in a 326-line SKILL.md. Sections are well organized, but content that clearly belongs in a separate reference (the upgrade procedure and output schema) is inline with no one-level-deep references, matching anchor 3; not 4 because there is no appropriate file split at all, and not 2 because the body has clear headers rather than being an unstructured dump.

3 / 5

Total

17

/

20

Passed

Description

43%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 highly precise about when NOT to invoke the skill and virtually conflict-proof, but it fails to state what the skill actually does (evaluate, fix, comment on, and close failing review findings). Its trigger-value comes from gating rather than from discoverable natural-language keywords a user would say.

Suggestions

Lead with a one-clause statement of what the skill does, e.g. "Evaluates and fixes open failing review findings, then comments on and closes the reviews via roborev" — this would lift completeness and specificity together.

Add natural trigger terms users would actually say — "review findings", "failing reviews", "open findings", "fix the review" — so discovery works beyond the literal slash command.

Compress the negative-gating clauses to one concise sentence and use the reclaimed space for the 'what' statement; the current description spends nearly all its tokens on exclusion rules.

DimensionReasoningScore

Specificity

The description states only invocation conditions ("Use only for a current operative request that explicitly invokes /roborev-fix") and names no concrete actions — nothing about evaluating findings, fixing code, commenting, or closing reviews. It matches anchor 2 (domain named, actions minimal/generic); not 3 because not even 1-2 concrete capabilities are listed.

2 / 5

Completeness

The 'when' is maximally explicit ("Use only for a current operative request that explicitly invokes /roborev-fix, or a direct Agent Hook instruction") but the 'what' is entirely absent — the description never says what the skill does. This is the anchor-2 case of 'when' present without 'what'; not 3 because a clear 'what' is required, and not 1 because the 'when' clause is fully explicit.

2 / 5

Trigger Term Quality

It contains the key triggers "/roborev-fix" and "Agent Hook instruction" plus "quoted, pasted, or historical text", but omits natural phrases a user would actually say such as "fix the review findings", "failing reviews", or "open findings". Some relevant keywords with missing common variations — anchor 3; not 4 because several natural trigger phrasings are absent.

3 / 5

Distinctiveness Conflict Risk

The trigger is a single unambiguous slash-command or Agent Hook invocation, and it explicitly rules out firing from quoted, pasted, or historical text. This is a clear niche with distinct triggers and minimal conflict risk — anchor 5.

5 / 5

Total

12

/

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
kenn-io/roborev
Reviewed

Table of Contents

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