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AC x402-compute

This skill should be used when the user asks to "provision GPU instance", "spin up a cloud server", "list compute plans", "browse GPU pricing", "extend compute instance", "destroy server instance", "check instance status", "list my instances", or manage x402 Singularity Compute / x402Compute infrastructure. Handles GPU and VPS provisioning with USDC payment on Base or Solana networks via the x402 payment protocol.

modbender/skill-library-mcp Agent Skills author: modbender MIT 14 files body ≈ 1 585 tokens Open the sourcegithub.com↗ analyzed 3 d ago

This skill should be used when the user asks to "provision GPU instance", "spin up a cloud server", "list compute plans", "browse GPU pricing", "extend…

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureAI 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
A
90/100
safety, quality, tests
Safety 60%
90
Quality 40%
89
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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.

Broad scope 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 skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 6

    ✓ No critical or high findings

    Medium and low: 6
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Read Write Edit Bash WebFetch
    • low Secrets in code secret-high-entropy-token scripts/solana_signing.py:21
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      USDC_MINT_SOLANA = "EPjF…t1v"
      quoted
    • low Secrets in code secret-high-entropy-token scripts/solana_signing.py:22
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      TOKEN_PROGRAM_ID = "Toke…5DA"
      quoted
    • low Secrets in code secret-high-entropy-token scripts/solana_signing.py:23
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      ATA_PROGRAM_ID = "ATok…knL"
      quoted
    • low Secrets in code secret-high-entropy-token scripts/solana_signing.py:25
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      RENT_SYSVAR_ID = "Sysv…111"
      quoted
    • low Secrets in code secret-high-entropy-token scripts/wallet_signing.py:19
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      USDC_ADDRESS = "0x83…913"
      quoted

    Files scanned: 14. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 63/100

    • 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
    • 30Running it twice. 5 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 85Steps. 9 steps, 1 vague phrases
    • 100Tools and files. Tools declared in frontmatter
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1585 tokens
    • low 10 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
    • -31 of 11 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 417: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 9 items
    • +4Has examples (7 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.