SKILLEMALL.ai

BB format-markdown

Summarize and format markdown files, then apply mkdocs/material-compatible structural spacing fixes for math, list, and table blocks. Outputs to {filename}_formatted.md by default.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 6 files body ≈ 4 708 tokens Open the sourcegithub.com analyzed 2 d ago

Summarize and format markdown files, then apply mkdocs/material-compatible structural spacing fixes for math, list, and table blocks.

As a process B 66/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, progress reporting

ProcedureWriting and documentsData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
78
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
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.
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token package-lock.json:106
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…GLw+xYSd…cqA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:317
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…5TF+OC5p…Jvi+BDqbkiG7h7u/9SI8…L9D+QG/6wSrTtXg==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:432
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…NqZ+ryke…PfA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:605
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "integrity": "sha5…MnP+OZqs…xwc+zfQE…Hjq+bh6q5F+Z8/cksrLFYWQQw==",
    quoted
  • low Secrets in code secret-high-entropy-token package-lock.json:748
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…GP2+v96H…6yi+nVmG…Jbw+9DD6g97+NV67Q==",
    detector

Files scanned: 6. 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")

Process rating: all ten parameters 66/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 60Failures and branches. 2 branches
  • 70Execution cost. Instruction body is 4708 tokens
  • 100Tools and files. No external tools needed
  • 100Steps. 80 steps
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state

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 180: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 80 items
  • +3Output format is stated explicitly
  • +4Has examples (14 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.