jp_lit_suggest_classification_codes

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

Annotations indicate non-read-only and non-destructive. The description adds details: it performs external reads and local bookkeeping writes, updates session history on cache hit, and creates/replaces local cache on miss or force_refresh. This is valuable context beyond 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 reasonably concise with two sentences. It front-loads the core purpose and includes usage guidance. The first sentence is somewhat dense but still readable. 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?

Given the tool's complexity (5 parameters, caching behavior, external API calls, session bookkeeping), the description covers key behaviors: external vs local operations, caching strategy, and return value format. It lacks explicit error handling or rate limits but these are not critical for basic usage.

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 coverage is 100% with detailed parameter descriptions. The description does not add significant new meaning for individual parameters beyond what the schema already provides. It does mention the return format (suggested_category_param and call example) which is helpful for usage.

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 clearly states the tool looks up NDC/NDLC classification codes from Web NDL Authorities given a subject term, and returns a suggested_category_param usable in CiNii Books category filter along with a call example. It also distinguishes itself by specifying what it does not do (reverse lookup or actual search), making its purpose unambiguous.

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 explicitly tells the agent when to use this tool versus siblings: use jp_lit_find_authority_terms_by_classification for reverse lookup (classification to subject) and jp_lit_search for actual document search. It also notes that external sources are not modified, guiding appropriate use.

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