SKILLEMALL.ai
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BD sparkbtcbot

Set up Spark Bitcoin L2 wallet capabilities for AI agents. Initialize wallets from mnemonic, transfer sats and tokens, create/pay Lightning invoices, pay L402 paywalls, manage deposits and withdrawals. Use when user mentions "Spark wallet," "Spark Bitcoin," "BTKN tokens," "Spark L2," "Spark SDK," "Spark payment," "Spark transfer," "Spark invoice," "L402," "Lightning paywall," or wants Bitcoin L2 capabilities for an agent.

modbender/skill-library-mcp Claude Code author: modbender MIT 9 files body ≈ 8 789 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Set up Spark Bitcoin L2 wallet capabilities for AI agents.

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationFinanceAI 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
84/100
safety, quality, tests
Safety 60%
90
Quality 40%
76
Run on models
none yet
Process rating
D
45/100
Unfinished process
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Risky intent medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The purpose itself is risky: wallets, browser password stores, offensive security. Even an honest implementation gives the agent access to things that cost money.

For the author

Explain in the description why the access is needed and how it is limited; add tests that show refusals on dangerous requests.

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 · 6

✓ No critical or high findings

Medium and low: 6
  • medium Risky intent intent-wallet-secrets SKILL.md:695
    Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target
    1. **Back up the seed phrase offline** — write it down on paper or use a hardware backup. If you lose the mnemonic, the funds are gone permanently.
  • low Secrets in code secret-high-entropy-token package-lock.json:202
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…OM6+DlUh…Vx5+K4Jn…Mx4/3CDT…oyQ==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:325
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-j+gKEx…ahh+s1F2HZ+wAce…RkU++ZWQr…uoQ==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:371
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…rvP+yUUf…4tH/iSSo…tEA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:412
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha512-+lF0B…kdX+94aG…d8c+B3KT…U6A==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:440
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…wr6+cbx+9Ohp…EEe+gR9u…9RA==",
    detector

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 8789 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "requires"
  • note frontmatter-key unknown frontmatter key "model-invocation"
  • note frontmatter-key unknown frontmatter key "model-invocation-reason"
  • note frontmatter-key unknown frontmatter key "homepage"

Process rating: all ten parameters 45/100

  • 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. 21 mutating operations with no state check
  • 40Execution cost. Instruction body is 8789 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
  • 85Steps. 68 steps, 1 vague phrases
  • 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 18 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

  • +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
  • +5Description quotes 9 example trigger phrases
  • +3Description length 425: enough signal without eating the budget
  • +4Structure: 58 headings
  • +3Step-by-step instructions: 68 items
  • +4Has examples (30 code blocks)

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