Teach the pricing engine

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

No annotations provided, so description bears full burden. It explains that recorded outcomes influence future quotes via 'pricing learning loop', but does not disclose side effects (e.g., overwriting, need for authorization) or potential destructive actions. Still, the learning effect is transparently communicated.

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?

Two sentences — compact, front-loaded purpose, no wasted words. Efficiently conveys both action and motivational context.

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 7 required parameters, no output schema, and no annotations, description explains high-level purpose and learning impact but lacks details like return format, error conditions, or handling of duplicate records. Adequate for straightforward use but gaps remain.

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 (14%) — only 'quotedRate' has a description. Description adds context (e.g., 'won/lost' maps to 'won' boolean, 'actual cost per sqft' maps to 'actualCostPerSqft') but omits 'margin' (calculated, not a parameter) and does not fully explain all enums. Adds meaning beyond schema for purpose but not for individual parameters.

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 it records job outcomes (won/lost, quoted rate, actual cost per sqft, margin) into a learning loop. Title 'Teach the pricing engine' reinforces purpose. Distinguishes from siblings like 'pricing_rates' (which likely returns rates) and 'quote_create' (which creates quotes).

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?

Description implies usage after a job outcome is known, tying to a learning loop. Does not explicitly state when not to use or compare to siblings like 'job_complete', but context is clear for a feedback tool.

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