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

With no annotations provided, the description discloses key behaviors: requires an EVM wallet header, free trial limit, and conditional behavior for report_sign_detectability (no additional cost when variance ratio > 20). It also implies a read-only analysis. Still, it omits potential side effects or data handling details, so it is not fully transparent.

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 well-organized: starts with purpose, then input/output, then optional flag, then auth and pricing. Every sentence adds value, but the opening metaphor 'Map the factorization terrain' is slightly vague and could be replaced with a more direct statement. Still, it is efficient and not redundant.

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 the tool's complexity (13 parameters, no output schema, no annotations), the description is incomplete. It does not cover most parameters, output structure, error conditions, or what 'cost' means in detail. The provided information is a good start but leaves too many gaps for an agent to invoke it correctly.

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 0% and the description only explains 'coupling' (preferred input formats) and 'report_sign_detectability'. The other 11 parameters including sample_size, task_type, cost_model, model_class, and accuracy_target are left entirely unexplained. This does not adequately compensate for the lack of schema descriptions.

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 a specific action: 'Map the factorization terrain of your model' and explains the input (coupling structure) and output (block-diagonal strategy with calibrated risk prediction). It directly answers the question 'How should I factorize, and what will it cost me?' which distinguishes it from siblings like diagnose or explain.

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 clear input selection guidance: 'precision matrix preferred for n>2; covariance matrix recommended if sign or CC information is needed.' It also mentions prerequisites like X-Wallet header and trial limitations. However, it does not explicitly contrast with sibling tools, so it misses exclusionary guidance.

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