get_post_examples

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

With no annotations, the description bears the full behavioral disclosure burden. It reveals the return limit ('Returns up to 3 examples') and adds a usage constraint ('never copy sentences from them'). The verb 'Retrieve' sufficiently implies a read-only operation for this kind of tool. It could optionally disclose more about the output shape, but that is already structurally represented by an output schema.

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?

Two sentences contain the entire message with no filler. The tool's value is front-loaded, followed by a practical example, a return limit, and a usage constraint. Every clause 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 single-parameter retrieval tool with an output schema available, the description covers what is returned, how to query, and a practical guardrail. The only omission is a note about the default parameter, but the schema already declares a default. The agent can select and invoke the tool with confidence.

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?

The schema has 0% description coverage on the only parameter, `query`, so the description must compensate. It does: the parameter can be used to search by topic, channel, or type, and an example value is given. It does not describe what empty input does, though schema's default value covers that reasonable.

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 starts with a specific verb and resource: 'Retrieve past posts with their outcomes'. It also adds the intended use, 'tone calibration', which makes the tool's function concrete. It is clearly distinguishable from siblings like search_guidelines and list_visual_templates because neither of those fetches example 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 tells the agent that querying can be by topic, channel, or type, with a concrete example ('linkedin annuncio'). It does not explicitly contrast with search_guidelines or list_visual_templates, but the purpose of tone calibration and the example query provide enough context. A score of 5 would require explicit when-to-use versus the sibling tools.

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