reach_research

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

With no annotations, the description carries full burden. It discloses parallel execution, merged Markdown output with per-source notes, and region parameter behavior. It does not mention error handling or rate limits, but the behavioral traits for a read-only research tool are adequately conveyed.

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 extremely concise: two sentences with an additional parenthetical for region. No redundant phrases, front-loaded with core purpose. Every sentence adds value.

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?

Given no output schema, the description provides reasonable completeness: explains output format (merged Markdown with per-source notes) and key parameter behavior. It doesn't detail error behaviors but is sufficient for typical use. Sibling context helps.

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 0%, so description must compensate. It explains the region parameter values clearly but does not describe the 'limit' parameter (integer default 8). The 'query' parameter is self-explanatory. Partial compensation, missing one param.

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 states it performs cross-platform research by fanning out queries in parallel across specified sources (web, Hacker News, news, YouTube, etc.). It distinguishes itself from sibling tools like reach_search (likely single-platform) by emphasizing the multi-source parallel approach.

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?

While the description implies use for broad research across multiple platforms, it lacks explicit guidance on when to use this tool versus alternatives like reach_search or reach_hot. No when-not scenarios or alternative recommendations are provided.

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