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BD openclaw-claude-batch

Claude Batch API for processing large volumes of requests asynchronously with 50% cost savings. Use for bulk content generation, data analysis, content moderation, batch evaluations, or large-scale testing where immediate responses are not required.

modbender/skill-library-mcp Agent Skills author: modbender MIT 13 files body ≈ 1 072 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Claude Batch API for processing large volumes of requests asynchronously with 50% cost savings.

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI 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
B
84/100
safety, quality, tests
Safety 60%
80
Quality 40%
91
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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 · 20

    ✓ No critical or high findings

    Medium and low: 20
    • low Secrets in code secret-high-entropy-token examples/README.md:98
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file)
      # Output: Batch ID msgb…V8d
      fixture
    • low Secrets in code secret-high-entropy-token examples/README.md:105
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file)
      python ../scripts/batch_monitor.py msgb…V8d
      fixture
    • low Secrets in code secret-high-entropy-token examples/README.md:108
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file)
      python ../scripts/batch_runner.py status msgb…V8d
      fixture
    • low Secrets in code secret-high-entropy-token examples/README.md:117
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file)
      python ../scripts/batch_runner.py results msgb…V8d
      fixture
    • low Secrets in code secret-high-entropy-token examples/README.md:120
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file)
      python ../scripts/batch_runner.py results msgb…V8d -o results.jsonl
      fixture
    • low Secrets in code secret-high-entropy-token README.md:51
      High-entropy token-like string (may be an id, hash or a credential)
      # Output: Batch ID (msgb…V8d)
    • low Secrets in code secret-high-entropy-token README.md:58
      High-entropy token-like string (may be an id, hash or a credential)
      python scripts/batch_monitor.py msgb…V8d
    • low Secrets in code secret-high-entropy-token README.md:61
      High-entropy token-like string (may be an id, hash or a credential)
      python scripts/batch_runner.py status msgb…V8d
    • low Secrets in code secret-high-entropy-token README.md:68
      High-entropy token-like string (may be an id, hash or a credential)
      python scripts/batch_runner.py results msgb…V8d -o results.jsonl
    • low Secrets in code secret-high-entropy-token README.md:120
      High-entropy token-like string (may be an id, hash or a credential)
      python scripts/batch_runner.py status msgb…V8d
    • low Exfiltration read-dotenv README.md:319
      Reads a .env file
      export $(cat .env | xargs)
    • low Secrets in code secret-high-entropy-token references/api-overview.md:62
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "id": "msgb…V8d",
      quoted
    • low Secrets in code secret-high-entropy-token scripts/batch_monitor.py:7
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python batch_monitor.py msgb…V8d --interval 60
      quoted
    • low Secrets in code secret-high-entropy-token scripts/batch_monitor.py:8
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python batch_monitor.py msgb…V8d -o monitoring.jsonl
      quoted
    • low Secrets in code secret-high-entropy-token scripts/batch_monitor.py:173
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python batch_monitor.py msgb…V8d
      quoted
    • low Secrets in code secret-high-entropy-token scripts/batch_monitor.py:176
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python batch_monitor.py msgb…V8d --interval 30
      quoted
    • low Secrets in code secret-high-entropy-token scripts/batch_monitor.py:179
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python batch_monitor.py msgb…V8d -o monitor.jsonl
      quoted
    • low Secrets in code secret-high-entropy-token scripts/batch_runner.py:264
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python batch_runner.py status msgb…V8d
      quoted
    • low Secrets in code secret-high-entropy-token scripts/batch_runner.py:266
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python batch_runner.py cancel msgb…V8d
      quoted
    • low Secrets in code secret-high-entropy-token scripts/batch_runner.py:267
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      python batch_runner.py results msgb…V8d -o results.jsonl
      quoted

    Files scanned: 13. 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 46/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 85Steps. 17 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1072 tokens

    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 249: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 17 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 3 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.