WIA Braille + WIA Talk

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld=false, so the safety profile is covered. The description adds genuinely non-structured behavior: it returns IPA plus braille cells and quality/confidence scores, and low-quality results are flagged rather than hidden. That return-value behavior matters because there is no output schema.

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 conversion and the crucial caveat about non-official braille, then the return/quality behavior. Slightly padded by the Korean sentence that restates the English content rather than adding new information, which costs a point.

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?

With no output schema, the description usefully summarizes the return shape (IPA, braille cells, quality), and the annotations cover safety. Nothing essential for calling the tool is missing, though a supported-language pointer would have closed the only real gap.

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 100%, so every parameter (dots, lang, text) is already documented, including the 6-dot/8-dot distinction and the braille_languages referral. The description merely restates the two dot forms and adds nothing about lang or text handling, so baseline 3 is appropriate.

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 and resource (converts text to WIA Braille) and pins down the variant with the parenthetical 'pronunciation-based common braille (NOT an official national braille code)', which separates it from the math/Nemeth and BRF siblings. It does not explicitly name or contrast any sibling tool, so routing still needs inference.

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 text-to-braille direction is implied clearly enough to know what this is for, and the 'not an official national braille code' note warns of a key limitation. But there is no when-to-use versus braille_math_nemeth or braille_to_brf, and the schema's own pointer to braille_languages for supported codes is not echoed in the description.

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 declare readOnlyHint, idempotentHint, destructiveHint=false and openWorld=false, so safety is covered. The description adds genuine extra context by clarifying the coverage is pronunciation-based rather than an official national braille code, which is materially important scope information.

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 English sentence is tight and informative; the function/resource come first. The Korean line is a translation rather than new information, a mild redundancy, but reasonable for a bilingual audience.

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 informational tool with no output schema, the description adequately states what is returned (engine version and coverage counts) and qualifies the coverage semantics. Nothing critical is missing, though it could note the return shape more concretely.

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 zero parameters, so the baseline is 4. There is nothing for the description to clarify beyond what the empty schema already conveys.

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 and resource ('Returns the WIA Braille engine version and language coverage counts'), and the parenthetical clarifies the scope of the braille data it reports. It does not explicitly name the sibling it replaces (e.g. braille_languages), so an agent must infer the distinction, keeping this just below a 5.

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?

No explicit when-to-use, when-not-to-use, or named alternative is given; the agent can only infer that this is the call for engine version and coverage metadata. Implied usage only, which fits the 3 anchor.

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 (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the bar is lower. The description still adds meaningful context beyond them: the pronunciation-based rather than official-code semantics, and that each language entry shows conversion sources (rules, dictionary, espeak). No pagination or ordering behavior is disclosed, keeping it below a 5.

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?

Two short sentences, front-loaded with the core purpose and the important semantic caveat. The trailing Korean translation duplicates the English rather than adding information, which is a minor inefficiency but not harmful.

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 an optional-parameter, no-output-schema lookup tool, the description covers what is returned (per-language conversion sources) and the key semantic distinction from real braille codes. Combined with full schema coverage and rich annotations, only fine-grained ordering/pagination detail is missing.

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 100%, so both the limit cap/default and the query example (korean, ko) are already documented in the schema. The description adds no further parameter meaning, so the baseline 3 applies.

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 pair (lists/searches) and resource (languages the WIA Braille engine can convert), and immediately disambiguates it from the conversion siblings by clarifying it is pronunciation-based, NOT an official national braille code. An agent can distinguish it from braille_convert without opening either schema.

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: searching for a language code or name is the obvious precursor to braille_convert, but the description never says when to call this versus braille_engine_info or the other siblings, nor any exclusions. Adequate but leaves routing to inference.

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?

Adds real context beyond the annotations: the underlying engine is pronunciation-based and NOT an official national braille code, which warns the agent about output fidelity. Annotations already cover the safe/idempotent/closed-world profile, so this caveat is the meaningful addition. It still does not describe output shape or failure modes.

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 verb and scope, and the caveat is placed before the scope guidance. The Korean translation restates the first sentence rather than adding value, a small redundancy.

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 single-parameter, annotation-covered conversion tool with no output schema, the description covers purpose, input example, scope limit, and fidelity caveat. It leaves the exact return representation slightly implicit, but nothing critical to a correct invocation is missing.

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?

Only one parameter and schema coverage is 100%, so the schema already documents `text` fully, including the same example used in the description. The description adds no syntax, formatting, or constraint detail (e.g. what counts as 'linear') beyond the schema.

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 and resource: converts a linear math expression to Nemeth-code braille cells, with a concrete input example. It scopes itself to linear expressions, which implicitly separates it from the generic braille_convert sibling, but it never names that sibling explicitly.

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?

"Best for linear expressions; complex 2D layouts need reviewer post-processing" gives a clear use condition plus an exclusion. It stops short of pointing the agent at an alternative tool for the excluded case, so it is not a full 5.

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 declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: 8-dot cells are down-converted to 6-dot and reported, and the line/page wrapping is pronunciation-based rather than a certified national braille code — an important caveat for an agent choosing this tool.

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?

Two tight sentences with the core conversion stated first, followed by the important caveat about the wrapping algorithm. The appended Korean translation duplicates content but is a deliberate localization line rather than padding.

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 stateless read-only transform with full annotation coverage and fully documented parameters, the description covers input expectations, output encoding, and the wrapping caveat. The absence of an output schema leaves the shape of the 'reported' 8-dot conversion only vaguely described, which is the one small gap.

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 100% and every parameter carries its own description with ranges and defaults, so the baseline is 3. The description references wrapping behavior that maps loosely to cellsPerLine/linesPerPage but adds no syntax or interaction detail beyond the schema.

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 and resource ('Converts Unicode braille cells to BRF') and clarifies the output format is NABCC 6-dot ASCII braille read by embossers. An agent can distinguish it from braille_verify_brf (validation) or braille_convert (unspecified scope), though no sibling is named explicitly.

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?

No explicit when-to-use or when-not guidance, and no alternative tools are named despite several plausible siblings (braille_convert, braille_verify_brf). Usage must be inferred from the title's 'embosser file text' hint alone.

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 the description adds genuinely new behavioral context: the precise scope of the 9 checks, the explicit exclusions, and the important caveat that the result is pronunciation-based rather than an official national braille code. That caveat materially affects how an agent should interpret the output.

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 core purpose is front-loaded in the first clause, and the exclusion/caveat follows compactly. The Korean translation line adds length without new information for most callers, a minor redundancy, and the parenthetical ellipsis leaves the check list open-ended.

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?

With no output schema, the description partially compensates by listing what is analyzed and what is out of scope, which is enough for an agent to decide whether to call it. It stops short of describing the result shape (per-check pass/fail structure), which is the remaining gap for a verification tool.

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?

Only one parameter and schema description coverage is 100%, with the schema itself stating 'BRF text (ASCII braille)' and length bounds. The description adds no format guidance (e.g., encoding, line-ending expectations) beyond what the schema already says, so baseline 3 applies.

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 and resource ('Runs 9 automatic checks on BRF text') and enumerates the check categories (mapping, line length, page length, CRLF, form feed, round trip). This clearly distinguishes it from the conversion siblings (braille_convert, braille_to_brf), which transform rather than validate.

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 — validate BRF output produced elsewhere — and the description draws a boundary by saying what is NOT checked (paper quality, dot depth). But it never names an alternative tool or states an explicit when-to-use condition, so the agent must infer that this is a post-conversion validation step.

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 readOnly/idempotent/non-destructive, so the bar is lower, yet the description adds real behavioral context: unknown codes are reported as missing rather than hallucinated, codes are sound-units not sign language, and output is pronunciation-based rather than an official national braille standard. These are meaningful expectations an agent could not derive from annotations alone.

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-loads the core operation and its most important caveats efficiently. The parenthetical disclaimers and the bilingual Korean line add length but each carries distinct meaning; minor clutter, not waste.

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 two-param, read-only conversion tool with no output schema, the description warns about missing codes, the sound-unit scope, and the non-official braille caveat. The only gap is it doesn't describe the shape of the returned IPA/braille output, which is a minor omission given the annotations.

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%, so both parameters (lang, codes) are already self-documenting, including the auto-detect behavior and the pointer to braille_languages. The description repeats the code format example but adds no semantics beyond the schema, so baseline 3 applies.

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 and resource (converts WIA Talk ISP codes back to IPA and WIA Braille) with a concrete code example. The reverse-direction sibling talk_text_to_gesture_codes is implicitly distinguishable from the stated direction, so an agent can route correctly.

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 context is implied by the directionality (codes → text) and the 'unknown codes are listed as missing, never invented' note, but the description never explicitly names the alternative sibling or when to prefer this over talk_text_to_gesture_codes. Guidance is inferable rather than stated.

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 declare readOnlyHint, idempotentHint and destructiveHint=false, so safety is covered. The description still adds meaningful domain behavior beyond that: the output concerns sound-unit codes only, not sign language, and the codes are pronunciation-based rather than an official national standard. Return shape/pagination is not described, but the domain scope clarification is genuinely additive.

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 statement and the two disambiguating parentheticals, with the bilingual Korean line at the end. Every line earns its place, though the mirrored Korean sentence adds length without new information for a non-Korean reader.

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?

With no output schema, the description carries the return-value burden and adequately conveys that the result is the set of covered sound segments. A tool this simple needs little more, though a one-line note on result form (flat list vs grouped) would fully close the gap.

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 zero parameters, so the baseline of 4 applies. The description correctly implies a parameterless, whole-corpus listing with no filtering syntax to explain.

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 ("Lists") and resource ("braille/IPA segments currently have a WIA Talk ISP code"), and immediately narrows scope with "Sound-unit codes, not sign language" and "pronunciation-based, NOT an official national braille code." An agent can distinguish this from talk_codes_to_text and talk_text_to_gesture_codes without opening any schema.

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 the use case (checking which segments are covered by a Talk ISP code) but never states when to call this versus a sibling such as talk_codes_to_text. No preconditions or alternatives are named, so usage is inferred rather than guided.

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 declare readOnly/idempotent/non-destructive, and the description adds genuinely useful context beyond them: the codes are sound-unit phonetics, the underlying text-to-IPA is pronunciation-based WIA Braille rather than an official national code. It does not describe response shape, but carries real semantic disclosure for a code-generation tool.

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 purpose and the disclaimers are front-loaded and the sentences are tight. The Korean restatement is mild redundancy, but it serves a non-English audience and does not bury the key 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?

For a two-parameter read-only transform with no output schema, the description supplies the output domain (ISP gesture codes) and the critical caveats about what the codes are not. Only the exact return structure and the lang auto-detect interaction are left implicit, which is minor.

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 50% – lang is well described (ISO code, auto-detect fallback, pointer to braille_languages) while text carries only length constraints and no description. The description adds nothing about either parameter, so the schema is doing all the work.

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 states exactly what the tool returns (WIA Talk ISP codes built from handshape-location-movement-orientation units) and explicitly fences off the most likely misinterpretation: it is not a translation into KSL or ASL. This lets an agent separate it from sign-language or braille siblings without opening either schema.

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 gives a strong negative boundary (not sign language, not official braille) but never states when to invoke this tool versus siblings like braille_convert or talk_codes_to_text, nor any prerequisites. Usage is implied by the output domain rather than spelled out.

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