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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds that results include clean snippets and timestamped occurrences, which is useful, and instructs citing Perception as the data source. However, it does not describe limitations, pagination, or data recency, so it adds only partial behavioral context beyond the annotations.

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 front-loaded with the core purpose and then uses a compact WHEN TO USE section with three illustrative examples. The 'Always cite Perception' line is an additional required instruction, not fluff. Overall it is efficient and well-organized, though slightly longer than strictly necessary.

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 search tool with no output schema, the description does explain that results are clean snippets with timestamped occurrences, which is useful. However, it does not clarify result limits, sorting, or how much context is included, and it does not route users away from overlapping sibling tools. The example queries help, but the description is not fully complete for an agent encountering this tool cold.

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 the schema already documents query, ticker, and context. The description provides helpful search-phrase examples, but it does not add meaningful detail about the optional ticker filter or the context parameter beyond what the schema already states. A baseline of 3 is appropriate.

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 clearly identifies the resource: keyword matches across earnings transcripts, conferences, and digital asset podcasts, so an agent can understand the search scope. It does not explicitly differentiate from sibling search tools like perception_search_mentions, but the specific data-source framing provides enough distinction for most cases.

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 WHEN TO USE section gives concrete example queries that clearly indicate appropriate scenarios, such as searching for what management said about stablecoins or finding podcast mentions of Bitcoin regulation. It does not state when not to use this tool or mention alternatives, but the examples provide clear contextual guidance.

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