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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. Beyond that, the description adds valuable context: the cost per call, that pre-existing transcripts/visual analyses are included 'at no extra cost', and the detailed structure of the visual analysis (scene-by-scene breakdown with timing, on-screen text, etc.). This goes well beyond what the annotations convey.

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 sentences cover the core function, optional inclusions, related tools, workflow, and cost. Each sentence earns its place; there's no fluff or redundancy. The most critical information (the verb 'Fetch' and resource) is front-loaded.

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 fetch tool with no output schema, the description thoroughly covers the response payload (views, likes, engagement rate, outlier scores, etc.), optional cached data, and how to trigger new enrichment. It also gives a clear workflow ('Use after search_outliers'), making it complete for its intended purpose.

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?

Since schema description coverage is 100%, the baseline is 3. The description adds context by explaining that `includeTranscript` and `includeVisualAnalysis` pull from cache ('When a transcript or visual analysis already exists it is included at no extra cost') and that new generation is delegated to other tools, which clarifies the default behavior. However, the schema already conveys the core meaning of these flags, so the added value is incremental.

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 opens with 'Fetch a single post by id' – a specific verb, resource, and scope. It clearly enumerates the returned data (views, likes, comments, engagement rate, outlier scores, thumbnail, owning profile) and distinguishes itself from sibling tools like `search_outliers` (which is for searching/listing) and `get_profile` (which targets profiles, not posts).

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 explicitly states, 'Use after search_outliers to deep-dive a result,' providing a direct workflow context. It also points to `request_transcript` and `request_visual_analysis` for new enrichment, unambiguously indicating when NOT to use this tool. The cost note ('1 credit per call') further guides the agent's decision-making.

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