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AC agent-weave

Master-Worker Agent Cluster for parallel task execution. Use when building distributed agent systems with parallel processing needs, task orchestration, or MapReduce-style workflows.

ClawHub Agent Skills author: gl813788-byte v1.0.0 21 files body ≈ 433 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorAI and agentstype 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
A
91/100
safety, quality, tests
Safety 60%
95
Quality 40%
84
Run on models
none yet
Process rating
C
53/100
Has gaps
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

    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:70
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "integrity": "sha5…FSj+bWLt…2sH/Kn8E…h6w==",
      quoted
    • low Secrets in code secret-high-entropy-token package-lock.json:181
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "integrity": "sha5…Loy/Rxalv2kr+lqMlUnrDWV+3j4p…IHu+HtC7…g8A==",
      quoted
    • low Secrets in code secret-high-entropy-token package-lock.json:202
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "integrity": "sha5…CpK+FtMRQVdIMN6/Df5j…tIC+7KYK…qaA==",
      quoted
    • low Secrets in code secret-high-entropy-token package-lock.json:326
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "integrity": "sha512-l+sSef…kmC+4EH2…jvA==",
      quoted
    • low Secrets in code secret-high-entropy-token package-lock.json:339
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "integrity": "sha5…q1F+ppbRo70+YeaD…NPN+GD6b…CXQ==",
      quoted

    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 53/100

    • 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
    • 100Tools and files. No external tools needed
    • 100Steps. 11 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 433 tokens
    • 100Running it twice. No mutating operations

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 182: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 11 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    Agent Weave appears to be a local master-worker task orchestration skill with expected logging and worker-management behavior, not evidence of theft, hidden execution, or destructive activity.
    LLM: benign (high) · VirusTotal: benign · 27 May 2026