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AC maestro-sdk

Build AI agents that operate Solana vaults using the Maestro SDK (@trionlabs/maestro-sdk). Use when creating agents that transfer tokens, swap, or interact with policy-controlled vaults.

ClawHub Agent Skills author: yamancan v0.1.0 MIT-0 2 files body ≈ 1 946 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 58/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI 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
A
92/100
safety, quality, tests
Safety 60%
98
Quality 40%
84
Run on models
none yet
Process rating
C
58/100
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

    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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token SKILL.md:24
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      const USDC_MINT = new PublicKey("4zMM…cDU"); // devnet
      quoted
    • low Secrets in code secret-high-entropy-token SKILL.md:29
      High-entropy token-like string (may be an id, hash or a credential) (documentation table row)
      | Devnet | `BFLP…rSt` | `4uYW…RP2` |
      table

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 58/100

    • 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. 15 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 100Tools and files. No external tools needed
    • 100Steps. 15 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1946 tokens
    • 100Progress reporting. Reports progress
    • 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

    • +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 186: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 15 items
    • +4Has examples (8 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    The skill is coherent as a Maestro Solana vault assistant, but it gives the agent broad financial authority with automatic key setup, persistent state, and transfer paths that need tighter user confirmation.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026