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

Annotations already mark the tool read-only, open-world, and idempotent, but the description adds substantial behavioral context: it returns a findings packet with verbatim evidence, confidence, source, fetched_at, and stable pipeworx:// citations, lists explicit gaps[] for unanswered facets, and states latency expectations. It also explains depth-dependent behavior like gap-recovery and contradiction scans. No statement conflicts with 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 and information-dense, opening with account requirements and the ask_pipeworx alternative. However, it is not tight: 'Return type: a findings packet' and 'Also returns contradictions[] for standard/thorough' repeat facts already stated earlier, and the depth details partially duplicate the schema's enum description.

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 complex research tool with no output schema, the description covers all key operational facts: preconditions (account/paid tier), source scope, mechanism, return structure, gap behavior, contradictions, semantic excerpting, latency, and depth differences. An agent has enough context to select and invoke the tool correctly and to set expectations about results.

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?

The schema has 100% coverage, so the baseline is 3, and the two parameters are already documented. The description adds meaning by explaining depth implications ('quick=3, standard=3 with gap-recovery + contradictions, thorough=6 with iterative hop') and clarifying that the question should be natural language and can be broad/multi-part. This goes beyond the schema's enum descriptions.

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 states a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1540 STRUCTURED data sources' in one call, and explains that it decomposes questions into facets and routes them in parallel to 5,908 tools. It explicitly distinguishes itself from open-web search and from ask_pipeworx for single lookups, so an agent can tell it apart from siblings.

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 gives explicit when-to-use guidance ('Best for broad/multi-part questions over structured data') and when-not-to-use guidance ('For a single lookup use ask_pipeworx instead'; 'If you are not signed in, use ask_pipeworx instead'). It also warns about the paid 'thorough' depth and required account, which is an actionable prerequisite.

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