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BC Get eSIM Skill

Purchase eSIM data packages using USDC on Base Mainnet (or testnet for testing) via the x402 protocol.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 2 510 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Purchase eSIM data packages using USDC on Base Mainnet (or testnet for testing) via the x402 protocol.

As a process C 64/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

ProcedureWriting and documentsAI 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
88/100
safety, quality, tests
Safety 60%
96
Quality 40%
76
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • low Secrets in code secret-high-entropy-token esim_api.py:19
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "usdc_token": "0x83…913",
      quoted
    • low Secrets in code secret-high-entropy-token esim_api.py:27
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "usdc_token": "0x03…F7e",
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:182
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | USDC Token | `0x83…913` |
      table
    • low Secrets in code secret-high-entropy-token SKILL.md:191
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | USDC Token | `0x03…F7e` |
      table

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

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)

    Process rating: all ten parameters 64/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (Get eSIM Skill) differs from the folder (get-esim)
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 51 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Execution cost. Instruction body is 2510 tokens
    • low 16 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)
    • +3Description length 102: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Structure: 35 headings
    • +3Step-by-step instructions: 51 items
    • +4Has examples (8 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.