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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false. The description adds value beyond that by disclosing the exact composition of each result (explanation, section URL with anchor, cited docs links) and a staleness caveat about verifying syntax against current docs.

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 output contents are front-loaded in a single dense sentence, followed by a short caveat. Every clause carries information, though the first sentence is long and slightly list-heavy.

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?

An output schema exists, so return structure need not be re-explained, and annotations cover the safety profile. The description is sufficient for correct invocation, with only minor gaps around result ordering or freshness guarantees.

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 topic, lang and limit are already fully documented with examples and bounds. The description adds no syntax or format guidance beyond what the schema provides, so the baseline 3 applies.

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?

Names a specific resource (SQL, Python, CLI and config code blocks matching a topic) and details what each result carries. An agent can distinguish this from search_guide or get_chapter because the returned unit is explicitly code examples plus surrounding explanation.

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 phrase 'Runnable context for a coding agent' implies the use case, and the caveat about checking linked docs hints at freshness limits, but no sibling alternatives or when-not conditions are stated. Usage is suggested rather than prescribed.

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