chain_full_research

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

Annotations already declare readOnlyHint/idempotentHint, so safety is covered. The description adds value by disclosing the internal chain pipeline and the combined return structure (statutes, precedent statistics, interpretations, citations), which is behavioral context beyond annotations. No contradictions.

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 a one-line summary, then uses clear sections (Chains, Args, Returns, Examples). Every sentence adds useful information, and the structure is easy to scan.

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 the tool's complexity (chaining multiple research steps) and lack of an output schema, the description adequately explains the input parameters, return value, and provides usage examples. It is sufficient for an agent to select and invoke it correctly.

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 0%, so the description's Args section must compensate. It does: it explains query (with examples), display (results per sub-query), oc (optional override), and type (response format). While 'OC' is cryptic, overall it adds meaningful semantics beyond the bare schema.

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 opens with 'Complete legal research in one call' and enumerates a specific chain (AI search → statutes → precedents with outcome analysis → interpretations → citations), clearly stating it is the most comprehensive single-call research tool. This distinguishes it from sibling search and chain tools.

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 phrase 'most comprehensive single-call research tool' provides clear context for when to use it (comprehensive research), and examples show intended queries. However, it does not explicitly name alternative tools for simpler needs, so it lacks explicit exclusions.

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