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

Annotations declare readOnly/openWorld/non-idempotent, and the description adds substantial context beyond them: source list, per-source pagination/truncation with coverage_from, suppression of days under 20 authors, pricing at $0.01 per successful call, x402 payment placement in _meta, and free bad input/not-found behavior. This is exactly the operational detail an agent needs before invoking a metered, source-limited aggregation 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?

Front-loads the purpose and then packs source, truncation, suppression, and payment terms into dense clauses. It is longer than most definitions but every sentence carries operational information; minor tightening is possible but not required.

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?

No output schema exists, so the description must convey return shape—and it does: daily counts, distinct authors, mean sentiment, top 10 terms, coverage_from truncation, and suppression rule. It also covers payment mechanics and source availability, leaving little an agent would need to infer.

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 coverage is 100%, so both parameters are already documented. The description restates the 1-7 day window and adds that days beyond a source's reach truncate via coverage_from, but does not add meaningful syntax or interpretation beyond the schema for q or days. Baseline 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?

States a specific verb+resource: daily mention counts, distinct authors, mean VADER sentiment, and top co-occurring terms for a brand/product/topic over 1-7 days. It clearly distinguishes itself from raw-post siblings like x_search, reddit_search, and bluesky_search by emphasizing 'aggregate only, no text, no authors.'

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?

Gives clear context: use for aggregate sentiment/mention trends across Bluesky, Hacker News, Reddit, and X rather than raw post retrieval. It doesn't explicitly name alternatives or exclusion cases, but the aggregate-only framing strongly implies when to use it instead of sibling search tools.

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