SKILLEMALL.ai

BF loop-anything-skill

Improve important deliverables by looping them through multiple isolated AI reviewers, each evaluating from a different angle, until all reviewers give full approval (Score 120).

ClawHub Agent Skills author: Shin Yan v1.0.0 MIT-0 12 files body ≈ 2 715 tokens Open the sourceclawhub.ai analyzed 19 h ago

Improve important deliverables by looping them through multiple isolated AI reviewers, each evaluating from a different angle, until all reviewers give full…

As a process F 64/100 · Will not run — References files that are not bundled: templates/reviewer-packet.md, templates/reviewer-output.md, references/facet-patterns.md

AnalyzerData and analyticsAI and agentsWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
63
Run on models
none yet
Process rating
F
64/100
Will not run
References files that are not bundled: templates/reviewer-packet.md, templates/reviewer-output.md, references/facet-patterns.md
Tools and files w 18
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. 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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning missing-ref reference to a missing file: templates/reviewer-packet.md
  • warning missing-ref reference to a missing file: templates/reviewer-output.md
  • warning missing-ref reference to a missing file: references/facet-patterns.md
  • warning missing-ref reference to a missing file: references/runtime-compatibility.md
  • warning missing-ref reference to a missing file: templates/loop-run-manifest.json
  • warning missing-ref reference to a missing file: templates/issue-ledger.md
  • warning missing-ref reference to a missing file: templates/final-summary.md
  • warning missing-ref reference to a missing file: references/evidence-guide.md
  • warning missing-ref reference to a missing file: scripts/validate_loop_review.py

Process rating: all ten parameters 64/100

Will not run. References files that are not bundled: templates/reviewer-packet.md, templates/reviewer-output.md, references/facet-patterns.md
  • 0Tools and files. 9 referenced file(s) missing: templates/reviewer-packet.md, templates/reviewer-output.md, references/facet-patterns.md
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 8 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 55 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2715 tokens
  • low 12 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 178: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 55 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 63.

External checks

ClawHub: clean
This skill is a disclosed multi-review workflow that creates local review artifacts and runs a small local validator, with no evidence of deception, exfiltration, or destructive behavior.
LLM: benign (high) · VirusTotal: · 24 Jun 2026