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

Annotations already establish readOnlyHint, and the description adds helpful behavioral detail: it returns the closest notes with a short excerpt and link. This clarifies the output shape beyond the schema. The description does not contradict annotations.

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?

Three sentences cover purpose, return behavior, and usage guidance with no fluff. The core action is front-loaded, and every sentence earns its place.

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 one-parameter read-only search tool with an output schema, the description gives enough context: what to search, what to expect in results, and how to continue with get_field_note. Nothing critical is missing.

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%, so the baseline is 3, but the description adds meaning by scoping what the query should target: the author's product-planning, MVP-scope, and AI-agent notes. This helps an agent formulate better queries than the generic 'What to look for, in words' schema text alone.

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 names a specific verb and resource: searching Hovhannes Hovhannisyan's written field notes, with topic boundaries. It also distinguishes the tool by noting it returns the closest notes with an excerpt and link, setting it apart from get_field_note and list_field_notes.

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 gives an explicit usage trigger: 'Use this when asked what he has written or thinks about a product topic.' It also names get_field_note as the follow-up for reading a note in full. It does not explicitly contrast with list_field_notes, but the guidance is still clear and actionable.

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