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

No annotations are provided, so the description carries the behavioral disclosure burden. It clearly communicates a read-style operation ('Get') and specifies the response contents, including reaction/reply counts and any attachment. Pagination and auth are not discussed, but the core behavior and return shape are transparent enough for a straightforward fetch tool.

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 description is a single front-loaded sentence with no filler. It states the primary action first and then lists the return fields efficiently, earning every word.

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 simple three-parameter tool with a fully documented schema and no output schema, the description provides enough return-value detail to make the tool usable without ambiguity. Nothing critical is missing.

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 descriptions cover 100% of parameters, including pages, post_id, and get_sentiment, so the baseline is 3. The description adds little parameter-level meaning beyond the schema, though it reinforces that post_id is the required key and suggests the post_id source.

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 names the exact operation and resource: 'Get comments on a Facebook post by post ID.' It also enumerates the returned data (text, author details, reaction and reply counts, date, and attachment), making the tool's purpose concrete and distinguishable from platform-specific sibling comment tools.

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 clearly indicates when to use the tool: when comments are needed for a known Facebook post ID. The post_id parameter further contextualizes by naming the upstream Facebook post sources. It does not explicitly list exclusions, but there is no competing same-platform comment fetch tool among siblings.

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