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BC shop-culture

Agentic Commerce skills for the For the Cult store. Enables agents to browse and search for quality lifestyle, wellness, smart home, and longevity products, view details and variants, create orders with multi-chain payments (Solana, Ethereum, Base, Polygon, Arbitrum, Bitcoin, Dogecoin, Monero) or x402 checkout (USDC), apply CULT token-holder discounts, and track orders from payment to delivery. Use when a user wants to buy products, browse a store, find gifts, place an order, or track a shipment.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 5 550 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Agentic Commerce skills for the For the Cult store.

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureLogistics and warehouseAI 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
87/100
safety, quality, tests
Safety 60%
93
Quality 40%
78
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
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. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 7

✓ No critical or high findings

Medium and low: 7
  • low Secrets in code secret-high-entropy-token references/API.md:132
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    { "symbol": "USDC", "name": "USD Coin", "type": "spl", "decimals": 6, "mint": "EPjF…t1v" },
    quoted
  • low Secrets in code secret-high-entropy-token references/API.md:133
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    { "symbol": "USDT", "name": "Tether", "type": "spl", "decimals": 6, "mint": "Es9v…NYB" },
    quoted
  • low Secrets in code secret-high-entropy-token references/API.md:142
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    { "symbol": "USDC", "name": "USD Coin", "type": "erc20", "decimals": 6, "mint": "0xA0…B48" },
    quoted
  • low Secrets in code secret-high-entropy-token references/API.md:143
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    { "symbol": "USDT", "name": "Tether", "type": "erc20", "decimals": 6, "mint": "0xdA…ec7" }
    quoted
  • low Secrets in code secret-high-entropy-token references/API.md:464
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "tokenMint": "EPjF…t1v",
    quoted
  • low Secrets in code secret-high-entropy-token references/CHECKOUT-FIELDS.md:135
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "wallet": "7xKX…AsU",
    quoted
  • low Secrets in code secret-high-entropy-token references/CHECKOUT-FIELDS.md:153
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "address": "7xKX…AsU",
    quoted

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5550 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 54/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 24 mutating operations with no state check
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5550 tokens
  • 100Steps. 66 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 12 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 501: enough signal without eating the budget
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 66 items
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.