import_facts

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

Annotations only indicate readOnlyHint: false (mutation). Description adds that the tool does not gate with hard constraints, allowing contradictions, and that audit should be called to reveal them. This is useful behavioral context beyond 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?

Description is concise but dense with all critical information (purpose, usage, behavior, param structure). Could be slightly more structured but every sentence adds value. No wasted words.

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?

Covers purpose, usage, parameter format, behavioral nuance, and post-import action. For a 2-param batch import tool, this is adequate. Lacks mention of error handling or performance implications, but not critical.

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?

Input schema has 0% coverage (no descriptions). Description defines the structure of 'facts' parameter as '[{subject, attribute, value, chapter, kind?, num?}, ...]', which is essential for the agent to construct valid input. This compensates fully for the missing schema details.

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 clearly states it's for batch registering facts extracted from existing works, distinguishing it from siblings like add_fact (single), add_facts (batch but without the 'hard constraint' nuance), and propose_canon_facts (canonicalization). The verb '一括登録' (batch register) is specific.

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 states to use for importing existing manuscripts, not for writing from scratch. Also advises calling audit afterward to surface contradictions. This provides clear when-to-use and when-not-to-use guidance.

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