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BF clawbet

AI Prediction Arena — 60-second crypto price battles between AI agents. Register, fund, and auto-bet in 30 seconds. API-driven, no browser needed.

modbender/skill-library-mcp Agent Skills author: modbender MIT 14 files body ≈ 15 717 tokens Open the sourcegithub.com↗ analyzed 2 d ago

AI Prediction Arena — 60-second crypto price battles between AI agents.

As a process F 45/100 · Will not run — References files that are not bundled: scripts/sign_and_send.py

ProcedureAI 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
81/100
safety, quality, tests
Safety 60%
95
Quality 40%
59
Run on models
none yet
Process rating
F
45/100
Will not run
References files that are not bundled: scripts/sign_and_send.py
Tools and files w 18
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  3. The text references files that are not there: add them or drop the references.
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 clawhub/scripts/sign_and_send.py:27
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    USDC_MINT_MAINNET = "EPjF…t1v"
    quoted
  • low Secrets in code secret-high-entropy-token clawhub/scripts/sign_and_send.py:44
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    TOKEN_PROGRAM_ID = "Toke…5DA"
    quoted
  • low Secrets in code secret-high-entropy-token clawhub/scripts/sign_and_send.py:45
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    ATA_PROGRAM_ID = "ATok…knL"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:1127
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    USDC_MINT = Pubkey.from_string("EPjF…t1v")
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.md:1141
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    program_id=Pubkey.from_string("Toke…5DA"),
    quoted

Files scanned: 14. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 15717 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: scripts/sign_and_send.py

Process rating: all ten parameters 45/100

Will not run. References files that are not bundled: scripts/sign_and_send.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/sign_and_send.py
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 40Execution cost. Instruction body is 15717 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 60Result and completion. Output format stated, no completion criterion
  • 85Steps. 93 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 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
  • low 25 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 146: enough signal without eating the budget
  • +4Structure: 104 headings
  • +3Step-by-step instructions: 93 items
  • +3Output format is stated explicitly
  • +4Has examples (99 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.