extract_key_terms

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable behavioral context: the extraction is deterministic (same document always yields same results) and uses regex and frequency rather than statistical NLP. This goes beyond the annotations by describing the method and consistency guarantees, which helps the agent trust the tool for reproducible use.

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 structured with a clear opening line stating the tool's function, followed by Args and Returns sections. It is not overly verbose; about 100 words in Korean. Key facts (determinism, regex usage) are front-loaded, and the parameter descriptions are wrapped into sections. A slight deduction for the Returns section being somewhat redundant with the output schema, but overall well-organized and efficient.

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?

The tool has a simple signature (2 parameters, 1 required) and an output schema that covers return structure, so the description does not need to detail return types extensively. It provides enough context for correct invocation: it names the parameters, explains the deterministic behavior, and notes the output categories (dates, numbers, frequent_terms). It lacks explicit usage guidance and error conditions, but these are minor gaps given the simplicity and existing annotations. Overall, it is sufficiently complete for an agent to call the tool 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 coverage is 100% for both parameters, so the baseline is 3. The description adds meaning beyond the schema: it clarifies that max_terms is 'per category' and notes it is 'for context protection' (컨텍스트 보호용), which explains the purpose of the limit. It also frames relative_path as a 'document relative path,' matching the schema but reinforcing usage. This extra insight justifies a score above baseline.

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 extracts dates, numbers with units, and frequency-based key term candidates from documents. It uses specific verbs ('extract') and resource types, and is distinct from siblings like extract_document_outline (which handles outlines) and read_document_chunk (which reads content). The purpose is immediately understandable without ambiguity.

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 implies usage for pulling key terms and metadata from a document, but it does not explicitly mention when to use this tool versus alternatives such as extract_document_outline or build_summary_prompt. No exclusions or alternative routing are provided, so an agent would need to infer context from sibling names rather than direct guidance.

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