SKILLEMALL.ai

CC yotta-code-quality

Pair-style code quality reviewer: twelve book-grounded decay risks (R1–R6, T1–T6) plus release-safety and first-paint UX checks. Findings always use Iron Law (Symptom → Source → Consequence → Remedy) and a 0–100 review-index Health Score. Triggers when: user asks to review code/PR/diff, "any issues", "ready to merge", smells, refactoring, tech debt, test quality, coverage, or architecture health; or says 「结对评审」/「发版前扫一眼」/ yotta-code-quality. Do NOT trigger for: greenfield "how do I write X" with no code, pure syntax questions, or tool/framework questions with no shared code.

Not recommendedcritical or high security findings
ClawHub Agent Skills author: YottaMeta v0.4.0 MIT-0 21 files · 1 script body ≈ 1 484 tokens Open the sourceclawhub.ai analyzed 27 h ago

Pair-style code quality reviewer: twelve book-grounded decay risks (R1–R6, T1–T6) plus release-safety and first-paint UX checks.

As a process C 60/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
C
73/100
safety, quality, tests
Safety 60%
59
Quality 40%
94
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 3

  • high Dangerous commands cmd-destructive-fs README.md:138
    Destructive filesystem command (wipes root/home/drive) (code comment)
    │   └── hooks.json            # optional: PreToolUse hooks for rm -rf / git push --force
    comment
  • high Dangerous commands cmd-destructive-fs README.zh-CN.md:151
    Destructive filesystem command (wipes root/home/drive) (code comment)
    │   └── hooks.json            # 可选:PreToolUse 拦截 rm -rf / git push --force
    comment
Medium and low: 1
  • medium Dangerous commands cmd-pipe-to-shell references/editorial-extensions.md:16
    Downloads and executes remote code from an unrecognised host (pipe to shell) (detector / deny-list definition)
    - `curl | sh` or equivalent in docs/scripts aimed at end users.
    detector

Files scanned: 20. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

✓ No remarks against the Agent Skills spec

Process rating: all ten parameters 60/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 60Failures and branches. 2 branches
  • 70When it triggers. States when to use, but not when not to
  • 85Steps. 18 steps, 3 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1484 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +5Description quotes 3 example trigger phrases
  • +3Description length 580: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 18 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (10 of 10)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

External checks

ClawHub: suspicious
This appears to be a legitimate code-review skill, but its installers can overwrite or delete through unsafe destination paths and can persist broadly in agent skill folders.
LLM: suspicious (high) · 8 Sept 2026