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BC json-repair-tool-pro

|- 功能涵盖: repair。

ClawHub Hermes author: 天轰穿 v1.0.0 MIT-0 2 files body ≈ 2 126 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

|- 功能涵盖: repair。

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
B
83/100
safety, quality, tests
Safety 60%
100
Quality 40%
57
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
When it triggers w 12
0
Inputs and preconditions w 11
0
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 · 0

✓ No critical or high findings

Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Not a YAML token: 功能涵盖: repair。 at line 8, column 17: description: |- 功能涵盖: repair。 ^^^^^^^^^^^^^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "edition"
  • note frontmatter-key unknown frontmatter key "tools"

Process rating: all ten parameters 56/100

  • 0Result and completion. Does not say what the result is
  • 0When it triggers. No condition that starts the skill
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 71 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2126 tokens
  • 100Running it twice. No mutating operations
  • low 18 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)
  • +3Description length 16: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 53 headings
  • +3Step-by-step instructions: 71 items
  • +4Has examples (5 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.

External checks

ClawHub: suspicious
The skill is mostly a JSON repair tool, but it needs review because it can run commands, automatically change many files, and includes loosely scoped callback/API behavior.
LLM: suspicious (high) · 29 Aug 2026