SKILLEMALL.ai

AF llm-judge

Use when comparing two or more code implementations against a spec or requirements doc. Triggers on "which repo is better", "compare these implementations", "evaluate both solutions", "rank these codebases", or "judge which approach wins". Also covers choosing between competing PRs or vendor submissions solving the same problem. Does NOT review a single codebase for quality — use code review skills instead. Does NOT evaluate strategy docs — use strategy-review. Requires a spec file and 2+ repo paths.

ClawHub Agent Skills author: Kevin Anderson v1.0.4 MIT-0 6 files body ≈ 2 575 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process F 56/100 · Will not run — References files that are not bundled: ../../../beagle-core/skills/llm-artifacts-detection/SKILL.md

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
F
56/100
Will not run
References files that are not bundled: ../../../beagle-core/skills/llm-artifacts-detection/SKILL.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

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 · 0

✓ No critical or high findings

Files scanned: 6. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../../../beagle-core/skills/llm-artifacts-detection/SKILL.md

Process rating: all ten parameters 56/100

Will not run. References files that are not bundled: ../../../beagle-core/skills/llm-artifacts-detection/SKILL.md
  • 0Tools and files. 1 referenced file(s) missing: ../../../beagle-core/skills/llm-artifacts-detection/SKILL.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 60Result and completion. Output format stated, no completion criterion
  • 65Failures and branches. 3 branches
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 30 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2575 tokens
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 14 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 5 example trigger phrases
  • +3Description length 505: enough signal without eating the budget
  • +4Structure: 28 headings
  • +3Step-by-step instructions: 30 items
  • +3Output format is stated explicitly
  • +4Has examples (12 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

External checks

ClawHub: clean
This skill is a coherent repo-comparison helper, but users should understand that its test-running step can execute code from the repositories they ask it to judge.
LLM: benign (high) · VirusTotal: · 1 Jun 2026