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BD phy-concurrency-audit

Static concurrency and race-condition auditor for Go, Java, Python, Node.js/TypeScript. Detects shared-state mutations without locks (Go map races, Java non-atomic increments, Python thread/asyncio shared lists), TOCTOU (time-of-check-time-of-use) patterns across all languages, sync.Mutex copied by value, WaitGroup.Add inside goroutines, SimpleDateFormat as instance field, double-checked locking without volatile, asyncio shared state without Lock. Maps findings to CWE-362 (race condition) and CWE-367 (TOCTOU). Zero competitors on ClawHub — not a single concurrency-audit SKILL.md in 13,700+ files.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 2 files body ≈ 5 471 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Static concurrency and race-condition auditor for Go, Java, Python, Node.js/TypeScript. Detects shared-state mutations without locks (Go map races, Java…

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerPeople and hiringtype 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
B
89/100
safety, quality, tests
Safety 60%
99
Quality 40%
75
Run on models
none yet
Process rating
D
42/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security SKILL.md:28
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - **Security impact**: TOCTOU races in file ops enable symlink attacks and privilege escalation (CWE-367)

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

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5471 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 35): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 42/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5471 tokens
  • 100Steps. 5 steps
  • 100Consistency. Name and required fields are in place

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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 603: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 5 items
  • +4Has examples (3 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.