gograph_sql

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

Annotations already mark it as readOnly and idempotent. The description adds context about freshness checks and retries in certain analysis modes, which provides additional behavioral insight beyond 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?

Well-structured with a clear opening sentence, then supplementary details. Slightly lengthy but each section (freshness, read-only, parameter, usage, return) 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?

Despite no output schema, the description specifies the return format: list with file, line, and enclosing function name. All necessary information for an AI to use the tool is present.

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% for the single parameter; the description reinforces its purpose with examples (e.g., 'SELECT', 'users'), adding practical guidance beyond the schema description.

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 uses a specific verb 'Find' and clearly identifies the resource: SQL query literals in Go source code. It distinguishes from sibling tools like gograph_schema and gograph_envs by stating when not to use this tool.

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 provides 'WHEN TO USE' and 'NOT TO USE' sections with concrete scenarios and alternative tool names. Also explains the optional 'term' parameter for filtering.

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