Phrase timeline

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

Annotations already declare readOnlyHint and openWorldHint, so safety is covered and the description adds real value by disclosing the returned aggregates. However, it omits the critical caveat that counts are computed over a bounded 'scan' of results rather than the full corpus, which materially affects how an agent should interpret the numbers.

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, front-loaded with what it counts and how, followed by a single purposeful use-case hint. No filler or restatement of the title.

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?

With 7 parameters, no output schema, and mid-level schema coverage, the description should say more about the result structure (per-bucket counts, how top authors are ranked) and about the filters and scan cap. What is present is accurate but leaves gaps an agent must guess at.

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?

At 57% schema coverage the description usefully maps the time bucketing to day/week/month/year (the enum has no schema description) and clarifies 'word or phrase' semantics for q. It says nothing about scan, since/until, from_user, or reply_to_user, leaving roughly half the parameters undocumented in both places.

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?

States a concrete verb (count) and resource (phrase occurrences over time) plus the output shape (first/latest use, top authors). An agent can distinguish this from ca_first_said or ca_who_talks_about by the aggregation, though the description never names those siblings explicitly.

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?

'Useful for tracing how an idea spread' implies a research/trend use case but gives no explicit when-to-use versus when-to-use-a-sibling guidance. There is overlap with ca_first_said (first use) and ca_who_talks_about (authors) that the description never resolves.

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