Sector View

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

Beyond the annotations (readOnlyHint, openWorldHint, destructiveHint=false), the description discloses important runtime behavior: warm=False makes no upstream requests, warm=True fans out quotes() with parallel batches, requests_made counts cache misses, and unknown sector names raise with the valid list. This adds meaningful transparency about side effects and performance.

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 dense but well-structured, with each sentence adding value: the one-line summary, the warm=False behavior, the warm=True behavior, the sector filtering/error case, and a concrete example. It is front-loaded with the core purpose and does not waste words.

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 an output schema exists, the description doesn't need to explain return shapes. It covers the parameter semantics, edge cases, caching/rate-limit behavior, and error handling. Nothing essential is missing for the agent to select and invoke the tool 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 description coverage is 0%, but the description fully compensates. It explains the exact meaning and consequences of warm, the behavior of sector including the 'Name' string format, the unknown-name error, and the example sector value 'Crypto/Digital Assets'. All two parameters are semantically covered.

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, actionable statement: 'Sector map (13 sectors, static validated classification) with per-sector size and live averages.' This clearly identifies the resource and the kind of data returned, and distinguishes it from sibling tools like token_list or quote by describing a sector-level aggregate view.

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 explicitly distinguishes warm=False and warm=True, telling the agent when to use the cheap snapshot versus the live data path, and explains the rate-limit-safe batching behavior. It also covers the sector filter and error behavior for unknown names, giving clear decision rules.

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