research_run

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

readOnlyHint=true already tells the agent this is a safe read operation. The description adds genuine behavioral context by stating the return shape (step summary plus the next call), which is a useful orchestration hint. It does not disclose what quick vs. standard budget changes, pagination, or limits on the 100k-char text input, so it stops short of rich disclosure.

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?

A single front-loaded sentence that states the action first and the return behavior second, with no filler. The long parenthetical enumeration is dense but earns its place by listing the supported domains.

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 an orchestration tool with seven parameters, 0% schema coverage, and no output schema, the description is too thin. It explains neither the required scenario/query contract nor the optional law, date, text, article, and budget inputs, so an agent cannot reliably construct a call from the description alone.

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% across seven parameters, so the description must compensate and largely does not. It paraphrases the scenario domains in Korean, loosely aligning with the scenario enum, but never mentions query, law, date, text, article, or the budget enum values quick/standard, leaving six parameters semantically opaque.

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 names a concrete function: bundling multi-step research per consultation-question type and returning a step summary plus the next call. The parenthetical enumerates the ten research domains (lease, subscription, redevelopment, brokerage, zoning, tax, contract, applicable law, statute map, amendment), which makes the scope tangible. However, it never distinguishes this orchestration tool from the many granular siblings (statute_find, article_get, source_search), so an agent cannot tell why it should pick this one.

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?

There is no when-to-use or when-not-to-use guidance and no mention of alternatives, despite eleven sibling tools that overlap heavily. The phrase '상담 질문 유형별' weakly implies it is for consultation-style multi-step questions, but nothing states the condition that selects this tool over calling the primitives directly.

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