SKILLEMALL.ai

CD 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.

garrytan/gbrain Agent Skills author: garrytan MIT 1 file body ≈ 1 643 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Quality gate via second model.

As a process D 41/100 · Unfinished process — References files that are not bundled: ../conventions/cross-modal.yaml, ../conventions/test-before-bulk.md, ../conventions/model-routing.md

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
99
Quality 40%
72
Run on models
none yet
Process rating
D
41/100
Unfinished process
References files that are not bundled: ../conventions/cross-modal.yaml, ../conventions/test-before-bulk.md, ../conventions/model-routing.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: gbrain

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security SKILL.md:124
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    auth bypasses, data leaks, privilege escalation paths.

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../conventions/cross-modal.yaml
  • warning missing-ref reference to a missing file: ../conventions/test-before-bulk.md
  • warning missing-ref reference to a missing file: ../conventions/model-routing.md
  • warning missing-ref reference to a missing file: ../conventions/agent-operator-protocol.md
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "mutating"

Process rating: all ten parameters 41/100

Will not run. References files that are not bundled: ../conventions/cross-modal.yaml, ../conventions/test-before-bulk.md, ../conventions/model-routing.md
  • 0Tools and files. 4 referenced file(s) missing: ../conventions/cross-modal.yaml, ../conventions/test-before-bulk.md, ../conventions/model-routing.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 100Steps. 37 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1643 tokens
  • low 11 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +3Description length 305: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 37 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.