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Vibes-Coded Agent Tools

by io.github.doteyeso-ops
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vc_attest

Read-onlyIdempotent

Sign a claim offline-verifiable (attest, 5c). Returns a signed attestation (Ed25519 + HMAC receipt).

Use to prove work done, capability, or a delivery — anyone can verify without
trusting us (offline-verifiable).
Sibling: vc_attest_verify, vc_agent_reputation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "claim_type": "<claim_type>",
      "statement": "<statement>"
    },
    "name": "vc_attest"
  }
}

Input Schema

NameRequiredDescriptionDefault
subjectNoClaim subject.
agent_idNoAgent making/attesting the claim.
statementYesThe claim itself.
claim_typeYeswork_done | identity | capability | observation | delivery | receipt | permission
payment_signatureNoOptional x402 PAYMENT-SIGNATURE if not using X-Vibes-Key.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds useful behavioral context beyond annotations: attestations are offline-verifiable, use Ed25519 plus an HMAC receipt, and do not require trusting the service. Annotations already signal readOnly, idempotent, and non-destructive behavior, so the description does not need to repeat those; there is no contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: core action and return format first, followed by use case and sibling pointers. Every sentence earns its place with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the full parameter descriptions and an output schema, the description is mostly complete: it states what the tool does, what it returns, when to use it, and names related tools. Minor gaps remain around explicit sibling differentiation and the meaning of '5c,' but these do not block correct use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 5 parameters. The description adds only marginal value by mentioning example claim types like 'work done, capability, or a delivery,' which partially overlaps with the claim_type description in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies a specific action and resource: 'Sign a claim' and 'Returns a signed attestation (Ed25519 + HMAC receipt).' It names sibling tools like vc_attest_verify and vc_agent_reputation, but does not explicitly explain how they differ, leaving some differentiation to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit use context: 'Use to prove work done, capability, or a delivery — anyone can verify without trusting us.' Sibling tools are named, but there is no explicit when-not-to-use guidance or direct comparison with alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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