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BF scout-commerce

Search for products on Amazon/shopify and buy with USDC on Solana. Swap tokens using Jupiter.

modbender/skill-library-mcp Agent Skills author: modbender MIT 11 files body ≈ 759 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Search for products on Amazon/shopify and buy with USDC on Solana.

As a process F 34/100 · Will not run — References files that are not bundled: url

ProcedureShopifySoftware developmentCommercetype 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
79/100
safety, quality, tests
Safety 60%
92
Quality 40%
59
Run on models
none yet
Process rating
F
34/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. 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 · 8

✓ No critical or high findings

Medium and low: 8
  • low Secrets in code secret-high-entropy-token scripts/balance.py:21
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    USDC_MINT = "EPjF…t1v"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/balance.py:86
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    {"programId": "Toke…5DA"},
    quoted
  • low Secrets in code secret-high-entropy-token scripts/balance.py:147
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "mint": "So11…112",
    quoted
  • low Secrets in code secret-high-entropy-token scripts/swap.py:25
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "SOL": {"address": "So11…112", "decimals": 9, "name": "Solana"},
    quoted
  • low Secrets in code secret-high-entropy-token scripts/swap.py:26
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "USDC": {"address": "EPjF…t1v", "decimals": 6, "name": "USD Coin"},
    quoted
  • low Secrets in code secret-high-entropy-token scripts/swap.py:27
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "USDT": {"address": "Es9v…NYB", "decimals": 6, "name": "Tether USD"},
    quoted
  • low Secrets in code secret-high-entropy-token scripts/swap.py:28
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "BONK": {"address": "DezX…263", "decimals": 5, "name": "Bonk"},
    quoted
  • low Secrets in code secret-high-entropy-token scripts/swap.py:29
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "TRUST": {"address": "F5sc…onk", "decimals": 6, "name": "TRUST"},
    detector

Files scanned: 10. 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 missing-ref reference to a missing file: url
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 34/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 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. 5 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 75Steps. 3 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 759 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)
  • +3Description length 93: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -31 of 8 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 3 items
  • +4Has examples (2 code blocks)

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