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BC agent-squad

Manage persistent AI coding squads that run in tmux sessions with task queues, progress reports, and automatic health monitoring. Use when the user wants to: (1) start/launch/create/restart a squad or team of AI agents, (2) assign/give tasks to a squad, (3) check squad status or ask what a squad is doing, (4) ping/nudge a squad to report progress, (5) stop a squad, (6) list all active squads, (7) configure squad settings like default project directory, (8) delete/archive a squad. Supports Claude Code, Codex, Gemini CLI, OpenCode, Kimi, Trae, Aider, and Goose as AI engines.

ClawHub Agent Skills author: 0xTimi v0.9.4 MIT-0 18 files · 10 scripts body ≈ 1 971 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Manage persistent AI coding squads that run in tmux sessions with task queues, progress reports, and automatic health monitoring.

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions

IntegrationAI and agentsSoftware developmentData and analyticstype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Tools and files w 18
60
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 · 0

    ✓ No critical or high findings

    Files scanned: 18. 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 58/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 65Failures and branches. 3 branches
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 17 steps, 2 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1971 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)
    • +3Output format is not stated: the model decides each time
    • -31 of 10 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 579: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 17 items
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (1 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    This skill appears to do what it says, but it starts unattended AI coding agents with broad project access and some status actions expose or alter live sessions.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026