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CC sandbox-selfheal-guard

(no description)

ClawHub Agent Skills author: orionshaowswmw v3.0.13 MIT-0 11 files · 4 scripts body ≈ 1 456 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

Sandboxes (Arena 128 MB/10k-file snapshots, containers) evict binaries and GGUF models; small scripts survive and call missing files → agents appear to "think

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
70/100
safety, quality, tests
Safety 60%
100
Quality 40%
25
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
30
the three weakest of ten parameters · all ten

How to improve

  1. Add a description to the frontmatter: without it the skill never triggers.
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: 11. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • error description-missing SKILL.md: no `description` — the skill can never trigger
  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Missing , or : between flow sequence items at line 6, column 45: categories: ["Agent Lifecycle categories: ["Agent Lifecycle categories: ["Agent… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • note frontmatter-key unknown frontmatter key "categories"

Process rating: all ten parameters 54/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
  • 100Steps. 16 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1456 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • 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

  • +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 0: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +2Single-language instructions
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 16 items
  • +3All 5 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 25.

External checks

ClawHub: suspicious
This self-healing local LLM helper is mostly disclosed and purpose-aligned, but review is warranted because repair mode can make privileged system changes and its source validation before rebuilding code is weak.
LLM: suspicious (high) · 7 Sept 2026