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

Annotations are minimal (readOnlyHint=false, destructiveHint=false), so the description carries the burden. It discloses important side effects: auto-creates the content plan when none exists, each suggestion lands in generating_brief, briefs forge automatically, and free-tier queue/forge-at-reset behavior. This is rich behavioral context, though it doesn't detail what happens on partial failures or how suggestionIds are returned (though it mentions they are returned).

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 dense but purposeful sentences. Critical preconditions and warnings are front-loaded, and every clause earns its place (duplicate handling, provenance, free-tier behavior). No fluff.

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 complexity (5 params, 4 required), minimal annotations, and no output schema, the description covers the workflow, side effects, and the return value. The only notable gap is the unexplained optional topicAngleTotal parameter and no explicit note on validation outcomes for invalid angles, but the coverage is strong overall for a complex tool.

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 0%, so the description is the only source of parameter meaning. It explains the relationship between signalObservationId and topicIndex (from list_radar_topics) and implies angles are the article suggestions. It doesn't explain the optional topicAngleTotal parameter, but the description still adds substantial meaning beyond the bare schema names for the key 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?

The description states a specific action ('Add'), a specific resource ('selected angles from a radar topic' to 'the content plan'), and mentions provenance preservation and duplicate skipping, which distinguishes it from siblings like add_article_suggestion or create_article_suggestion_with_input. This is a clear verb+resource+scope definition.

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 explicit preconditions ('call list_radar_topics first to get signalObservationId + topicIndex'), identifies the source tool for angles ('Angles come from expand_radar_topic'), and explicitly warns against a sibling ('do not also call generate_article_brief'). This proactively routes the agent and prevents misuse, going beyond mere context.

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