cal_lender_intel

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

No annotations are present, so description carries the burden. It explains the tool returns intelligence data and that passing intent can save tokens. While it doesn't disclose potential limitations like data freshness, the behavioral context is adequate for a read-only intelligence tool.

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?

Single paragraph is concise but well-structured: begins with purpose, then usage guidelines, then parameter advice. Every sentence adds value with no redundancy. Front-loaded with key information.

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 no output schema, the description explains the return content (strengths, watch-outs, etc.) and how to narrow response via intent. It covers all needed context for an agent to select and invoke the tool correctly, including relationship to sibling tools.

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 100% with good base descriptions. The description adds significant value: explains intent parameter with enum values and default, gives example usage ('e.g. intent="scenariosTheyLove"'), and clarifies that lenderSlug must match cal_lender_details. This goes well beyond the schema.

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?

Description clearly states the tool provides tribal-knowledge intelligence on a wholesale lender, listing specific aspects like strengths, watch-outs, speed notes, and AE contacts. It distinguishes from sibling tools by specifying usage after cal_lender_details and targeting qualitative questions.

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?

Explicitly says to use after cal_lender_details, for qualitative questions like 'is this lender any good for X?' or 'fastest path'. Provides examples of when to pass an intent to narrow response and save tokens, offering clear when-to-use and when-to-avoid guidance.

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