chapter_brief

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

Annotations declare readOnlyHint=true, and description confirms with '[read]'. Adds detailed behavioral context: return value structure, overdue setups, and purpose of reducing recall burden. 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?

Information is dense but mixed language (Japanese/English) and run-on structure. Could be more concise and better organized. Two sentences pack necessary info but at readability cost.

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, description thoroughly explains the return value categories and their contents. Parameters are simple and defaults are clear. Adequate for an agent to invoke correctly, though parameter definitions could be more explicit.

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 has 0% description coverage for parameters. Description mentions '第N章' linking to the chapter parameter and implies branch usage, but does not explicitly describe parameter roles or formats. Baseline 3 for missing coverage, with marginal added value.

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?

Description states it is a read tool that bundles canon before writing a chapter, listing specific return categories (characters, world, constraints, etc.). Clearly distinguishes from siblings like get_state by describing its composite nature.

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?

Explicitly says to call at the start of the writing loop to avoid multiple get_state calls, providing clear when-to-use and when-not-to-use guidance with an alternative named.

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