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cross-modal-review

Quality gate via second model. Spawn a different AI model to review work before committing. Includes refusal routing: if one model refuses, switch silently to the next. Extended in v0.25.1 with structured review-mode gating (when to invoke vs not) and a Codex code-review handoff for the diff-review case.

58

Quality

68%

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SecuritybySnyk

High

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tessl review fix ./skills/cross-modal-review/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

70%

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-structured, well-sequenced review workflow with clear validation gates and good file-level navigation, but it carries version-stamp verbosity and a redundant conformance-test section, and externalizes its key execution mechanic (model spawning) to files absent from the bundle.

Suggestions

Consolidate version metadata (v0.25.1, v0.27.x) into a single changelog/deprecated section or strip it from operational prose to improve conciseness.

Remove the duplicate conformance-test "Output Format" stub (lines ~195-197) or fold its intent into the existing "Output format" section to eliminate organizational clutter.

Add an in-body, concrete snippet for how the review model is selected and invoked (currently deferred entirely to an external conventions file not present in the bundle) to close the actionability gap.

DimensionReasoningScore

Conciseness

The body is mostly tight operational prose that assumes Claude's competence, but repeated time-sensitive version stamps ("v0.25.1", "v0.27.x") scattered through sections and a redundant conformance-test "Output Format" stub that duplicates the earlier "Output format" section add clutter, fitting score 2 (mostly efficient, could be tightened) rather than the lean score-3 anchor.

2 / 3

Actionability

Concrete elements exist (copy-paste output templates, numeric gating thresholds like "5+ files or 100+ lines"), but the core execution mechanic — how to spawn the review model — is externalized to conventions/model-routing.md (absent from this bundle) and the review step itself is stated as a directive ("Send the work + Contract") rather than executable instruction, matching score 2 (some concrete guidance, missing key details).

2 / 3

Workflow Clarity

The five Phases are clearly sequenced with an explicit validation checkpoint (Grade = Pass/fail with citations), an error-recovery/escalation path (refusal routing ending in user escalation), and a user-approval gate, matching the score-3 anchor of a clear sequence with explicit validation steps; it is above score 2 because checkpoints are explicit, not implicit or missing.

3 / 3

Progressive Disclosure

Content is organized into clearly headed sections with well-signaled, one-level-deep references to supporting materials (conventions/cross-modal.yaml, model-routing.md, test-before-bulk.md) and a concise body, matching the score-3 anchor of a clear overview with well-signaled one-level-deep references and easy navigation; it stays above score 2 because references are clearly signaled rather than vague.

3 / 3

Total

10

/

12

Passed

Description

67%

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 concretely states what the skill does and carves a distinct niche, but its trigger-term coverage skews technical and it lacks an explicit "Use when..." clause, capping trigger quality and completeness at the mid level.

Suggestions

Add an explicit "Use when..." clause with natural trigger phrases (e.g., "Use when you want a second opinion before committing significant or security-sensitive changes") so completeness can reach 3.

Surface user-natural keywords ("second opinion", "double check", "get another perspective") inside the description text itself, not only in the separate triggers field, to lift trigger-term quality.

Move or soften inline version stamps (v0.25.1, v0.27.x) out of the description; they are time-sensitive metadata that add noise without aiding trigger recognition.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions: "Spawn a different AI model to review work before committing", "if one model refuses, switch silently to the next", and a "Codex code-review handoff for the diff-review case", matching the score-3 anchor of multiple specific concrete actions rather than the single-domain score-2 anchor.

3 / 3

Completeness

The "what" is clearly stated, but the "when" is only described as a feature ("structured review-mode gating (when to invoke vs not)") with no explicit "Use when..." trigger clause, so per the guideline a missing explicit trigger clause caps completeness at 2 rather than 3.

2 / 3

Trigger Term Quality

It includes relevant terms ("review", "second model", "Codex") but leans technical ("quality gate", "refusal routing", "review-mode gating") and omits the natural phrasings users would say ("second opinion", "double check", "another perspective"), fitting score 2 (some relevant keywords, missing common variations) rather than the full-coverage score 3.

2 / 3

Distinctiveness Conflict Risk

The cross-modal/second-model pre-commit gate with refusal routing and Codex handoff is a clear niche with distinct framing unlikely to trigger for unrelated skills, matching the score-3 anchor rather than the overlapping score-2 anchor.

3 / 3

Total

10

/

12

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

relative_links

Relative link issues: 3 suspicious

Warning

Total

14

/

16

Passed

Repository
garrytan/gbrain
Reviewed

Table of Contents

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