Project testimonials

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

Annotations already establish readOnlyHint, idempotentHint, and non-destructive behavior, so the bar is lower. The description adds useful context beyond annotations by naming the source table, specifying returned fields, and implying fuzzy/keyword matching behavior, which aligns with the annotation profile.

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 compact and front-loaded with the core operation, followed by return fields, use case, and sibling alternative. Every sentence adds distinct value and none of the content is redundant with the schema.

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?

For a read-only, idempotent lookup tool with no required parameters and a full output schema, the description covers the essential decision context: what it does, what it returns, when to use it, and when not to. The sibling alternative and use case complete the picture.

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 100%, so the schema already documents all four parameters including their meanings and defaults. The description adds only light semantic context ('by slug or keyword', 'for a particular job') without exceeding what the schema offers, matching the baseline for full coverage.

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 begins with a specific verb-resource pair, 'Get customer testimonials tied to a specific project', and clarifies the lookup method ('by slug or keyword') and the data source ('from the testimonials table'). It also lists the returned fields, which distinguishes it from broader review 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?

It states an explicit use case: 'Use to source social proof or case-study quotes for a particular job.' It also gives a direct alternative and condition: 'For unfiltered reviews, use list_reviews,' providing clear routing guidance.

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