loaditout-mcp-server

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

With no annotations provided, the description carries the full burden and succeeds: it discloses the return format ('JSON array of proofs' with specific fields) and empty-state behavior ('Returns an empty array if no skills have been reported'). Does not mention auth or rate limits, but covers the essential behavioral traits.

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

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

Three efficiently structured sentences with zero waste: sentence 1 defines action and return structure, sentence 2 explains the concept, sentence 3 provides use cases and constraints. Information is front-loaded.

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

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

For a zero-parameter tool with no output schema and no annotations, the description is complete. It compensates for the missing output schema by detailing the return structure and fields, covers the empty state, and explains the conceptual model ('agent resume').

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

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

Input schema has 0 parameters (baseline 4). The description appropriately confirms 'No parameters required', providing clarity without unnecessary elaboration.

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

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

The description opens with a specific verb ('List') and resource ('execution proofs'), clarifies scope ('created by this agent'), and distinguishes from siblings by explaining the relationship to 'report_skill_usage' and defining what proofs are ('verifiable record of skill usage').

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

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

Provides explicit use cases ('review your usage history, share proof links, or verify your trust score') and notes the dependency on 'report_skill_usage' for data availability. Lacks explicit 'when not to use' contrasts with siblings like 'verify_proof', but effectively guides the workflow.

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