mcp_engram_leg_corpus

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

No annotations are provided, so the description must carry the full burden. It explains that the tool builds, verifies, or samples corpus batches, and mentions data sources and verification steps. However, it does not disclose side effects, idempotency, permissions, or rate limits, which are important for safe invocation of a training corpus builder.

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?

The description is two sentences long, front-loading the main purpose and then listing actions. Every sentence adds value without redundancy. It is concise and well-structured for quick parsing.

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?

Given 8 parameters, no output schema, and no annotations, the description covers the core workflow but lacks details on return values, error states, or the meaning of 'homotopy verify'. It is adequate for a technical user but not fully comprehensive for an AI agent.

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?

Schema coverage is low (13%), but the description adds meaning by explaining the action enum and the min_crs filtering. It does not explain parameters like coherence_min, limit, or persist_manifest in detail. The description partially compensates for low schema coverage but leaves gaps.

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 clearly states the tool's purpose: building a .leg training corpus as leg_block_pack_v1 batches. It specifies three actions (build, verify, sample) and mentions the selection criteria (CRS>=min_crs) and additional steps (scrub_export + homotopy verify). This is specific and distinct from sibling tools.

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?

The description outlines three actions and their functions, but does not provide explicit guidance on when to use this tool versus alternatives. There is no mention of prerequisites, conditions, or comparisons to sibling tools, leaving the agent to infer usage context.

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