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Privacy-first agent infrastructure providing forecasting, credential verification, settlement, and cross-rail transfers via x402 micropayments.

modbender/skill-library-mcp Agent Skills author: modbender MIT 5 files body ≈ 951 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Privacy-first agent infrastructure providing forecasting, credential verification, settlement, and cross-rail transfers via x402 micropayments.

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

AnalyzerData and analyticsAI and agentsInfrastructuretype 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
83/100
safety, quality, tests
Safety 60%
91
Quality 40%
72
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
0
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.
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 · 9

✓ No critical or high findings

Medium and low: 9
  • low Secrets in code secret-high-entropy-token README.md:147
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    target_address: "0x74…bEb"
    detector
  • low Secrets in code secret-high-entropy-token README.md:175
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - **PrivateClaimVerifier**: `0x1C…a3D`
    quoted
  • low Secrets in code secret-high-entropy-token README.md:176
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - **UnifiedPredictionSubscription**: `0x0d…80c`
    quoted
  • low Secrets in code secret-high-entropy-token README.md:179
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - **PrivateClaimVerifier**: `0xd4…38E`
    quoted
  • low Secrets in code secret-high-entropy-token README.md:180
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - **UnifiedPredictionSubscription**: `0x24…BBb`
    quoted
  • low Secrets in code secret-high-entropy-token skill.json:50
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "PrivateClaimVerifier": "0x1C…a3D",
    quoted
  • low Secrets in code secret-high-entropy-token skill.json:51
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "UnifiedPredictionSubscription": "0x0d…80c"
    quoted
  • low Secrets in code secret-high-entropy-token skill.json:54
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "PrivateClaimVerifier": "0xd4…38E",
    quoted
  • low Secrets in code secret-high-entropy-token skill.json:55
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "UnifiedPredictionSubscription": "0x24…BBb"
    quoted

Files scanned: 5. 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")

Process rating: all ten parameters 58/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 30Running it twice. 5 mutating operations with no state check
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 951 tokens
  • 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 143: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.