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loaditout-mcp-server

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verify_proof

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Instructions

Verify the authenticity and validity of an execution proof by its ID. Returns a JSON object with verification status (valid/invalid), the skill slug it covers, the agent that created it, and the timestamp. Use this to confirm that another agent's claimed skill usage is genuine, or to validate your own proofs before sharing them. Do not use this for listing proofs (use list_my_proofs instead).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
proof_idYesThe unique proof identifier to verify. Format: 'lp_' followed by 16 hex characters. Example: 'lp_a1b2c3d4e5f6g7h8'. Obtain proof IDs from report_skill_usage responses or list_my_proofs results.
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses return structure (JSON object with status, skill slug, agent, timestamp) and possible status values (valid/invalid). Minor gap: does not explicitly state if operation is safe/read-only or mention error conditions.

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?

Four sentences with zero waste: (1) purpose and return value, (2-3) usage scenarios, (4) exclusion constraint. Information is front-loaded and every sentence earns its place.

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

Completeness5/5

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

For a single-parameter verification tool, description is complete. Compensates for missing output schema by detailing return fields. Establishes clear relationship with sibling 'list_my_proofs'. No critical gaps given the tool's simplicity.

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 coverage is 100% with detailed parameter description including format ('lp_' + hex) and source. Description mentions 'by its ID' but does not add semantic meaning beyond what the schema already provides, which is appropriate for baseline 3.

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

Purpose5/5

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

Description opens with specific verb (verify) + resource (execution proof) + scope (by ID). Explicitly distinguishes from sibling tool 'list_my_proofs' via the exclusion clause, and implicitly contrasts with 'report_skill_usage' (creation vs verification).

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

Usage Guidelines5/5

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

Provides explicit when-to-use scenarios (confirm another agent's claimed usage, validate own proofs before sharing) and explicit when-not-to-use guidance ('Do not use this for listing proofs') with named alternative (list_my_proofs).

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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