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BB ship-loop

Run a chained build→ship→verify→notify pipeline for multi-segment feature work. Use when implementing multiple features in sequence, each as a coding agent task that gets committed, deployed, and verified before moving to the next. Prevents dropped handoffs between segments.

ClawHub Agent Skills author: Fernando v5.0.0 MIT-0 69 files · 7 scripts body ≈ 3 615 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

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
B
88/100
safety, quality, tests
Safety 60%
95
Quality 40%
77
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
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 docs/package-lock.json:211
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…SzS+cfgl…B0A==",
      detector
    • low Secrets in code secret-high-entropy-token docs/package-lock.json:322
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…cAz+ivBu…Lvw==",
      detector
    • low Secrets in code secret-high-entropy-token docs/package-lock.json:402
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…IxX/wd5n…MGF+pv6g…i2Z+Wnj9/KjGz…4Eg==",
      detector
    • low Secrets in code secret-high-entropy-token docs/package-lock.json:434
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha5…BQM/qZ3R+9TEU…es4+qu1b…BFA==",
      detector
    • low Secrets in code secret-high-entropy-token docs/package-lock.json:450
      High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
      "integrity": "sha512-8mL/vh8q…uJP+ZcVY…AJW+m0Et…WzA==",
      detector

    Files scanned: 54. 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 65/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 14 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 35 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3615 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 19 top-level sections: this looks like several domains in one skill

    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
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • -37 of 7 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 275: enough signal without eating the budget
    • +4Structure: 27 headings
    • +3Step-by-step instructions: 35 items
    • +4Has examples (11 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

    External checks

    ClawHub: suspicious
    Ship Loop is a disclosed automation tool, but it can autonomously modify, commit, push, deploy, clean repository state, run configured commands, and persist sensitive run context with limited safety gates.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026