WIHP: foreign text to Hangul

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds only the fixed size of the list (29 codes), which is minor context; it does not describe return shape or ordering, though a static enumeration needs little more.

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?

Front-loaded single English sentence that carries the key fact, followed by a short Korean gloss. The bilingual restatement is mildly redundant but compact and does not obscure the primary content.

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 a zero-parameter, read-only enumeration with no output schema, the description supplies exactly what an agent needs: what is listed and who consumes it. Nothing further is required to call it 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?

The tool takes no parameters, so the baseline is 4 per the rubric. Nothing in the description needs to compensate for a schema, and it correctly implies a parameterless enumeration.

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?

States a specific verb (List) and resource (29 language/variant codes) and explicitly ties them to the two sibling tools that consume them. An agent can immediately distinguish this from to_hangul and lookup_ipa.

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?

By naming to_hangul and lookup_ipa as the consumers, it makes the use case clear: call this to discover valid language codes before invoking those tools. No explicit when-not or negative guidance, but the routing context is strong.

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

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

Annotations already establish readOnly, idempotent, non-destructive, and closed-world behavior, so the bar is lower, and the description still adds real value: unknown words come back as found:false with ipa null and nothing is generated or guessed. That guarantees determinism beyond what the annotations say, though lookup/pagination mechanics go unmentioned.

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?

Front-loaded with the core action and sized in two short sentences, with the fallback behavior appended where it is most useful. The bilingual Korean sentence restates the same content, which is redundant for an English-reading agent but not wasteful enough to hurt.

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?

There is no output schema, so the description rightly carries the return-value burden and does explain the found:false/ipa null outcome. Nothing critical is missing for calling the tool correctly; only richer detail on the found-word response shape could improve it.

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%, so the description must compensate, and it partly does: 'up to 20 words' explains the words param and 'one language' explains lang. It does not mention that lang defaults to en_US or that 29 enum values exist, leaving an agent reliant on the schema to discover accepted language codes.

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?

States a specific verb (look up) and resource (IPA pronunciation) with scope: up to 20 words, one language, from WIHP's dictionary. It is clearly distinguishable in spirit from the siblings, but it never names list_supported_languages or to_hangul to rule out confusion, so sibling differentiation is only implicit.

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 batch limit of 20 words and the single-language constraint imply the intended use case, and the found:false note tells the agent what to expect for missing entries. However, there is no explicit statement of when to prefer this tool over siblings such as to_hangul or list_supported_languages.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description nonetheless adds genuine behavior context beyond them: determinism (same input, same output), the fallback of returning dictionary-missing words unchanged, and an explicit disclaimer that this is a rule-based rendering rather than an 'official/correct' transcription. It does not describe output shape or failure modes for bad/unsupported input.

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?

Front-loaded with the core verb+resource+mechanism, then compactly covers determinism, the caveat, and the missing-word fallback. The bilingual restatement adds length but serves a real audience purpose; still, the Korean line largely duplicates the English disclaimer rather than adding information.

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?

There is no output schema, so the description carries the burden of explaining results. It discloses the missing-word fallback and determinism but says nothing about the return shape (what 'Hangul' output looks like, whether IPA is included in the response, error behavior for unsupported source_lang). Adequate for a simple read-only transcriber, but with a clear gap on results.

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 67%, with text well documented and source_lang pointing to list_supported_languages, so the baseline is 3. The description's 'word -> IPA -> Hangul' segment adds indirect meaning to include_ipa, but it never names or explains include_ipa or source_lang explicitly, so it does not meaningfully exceed what the schema already provides.

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?

States a specific verb (transcribe) and resource (foreign word/short sentence into Hangul) and names the mechanism (WIHP dictionary + rule pipeline, word -> IPA -> Hangul). This is clearly distinguishable from siblings list_supported_languages and lookup_ipa, which are retrieval-only helpers this tool depends on.

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?

Usage is implied rather than stated: the pipeline explanation and the source_lang schema note ('see list_supported_languages') gesture at the workflow with the sibling tools, but the description never explicitly says when to use this versus lookup_ipa or what prerequisites exist. No when-not guidance is given.

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