reference

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

With no annotations provided, the description carries the full burden. It discloses what the tool returns (ISO positions, comparable grades, verification status per row) and adds an important caveat that comparable-at-ISO-position is only a trial starting point, not an interchangeability guarantee. This is more transparent than typical, though it does not cover all edge behaviors such as unknown grades.

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 sentences with no filler: the first sentence front-loads the purpose and output shape, and the second sentence adds the essential caveat. Every phrase earns its place.

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?

Even without an output schema, the description thoroughly explains what the agent should expect: ISO positions, comparable grades from other manufacturers, and per-row verification status. It also includes a critical usage caveat. For a two-parameter lookup tool, this is fully complete.

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% for both parameters, so the schema already documents 'brand' and 'grade'. The description adds example codes and reiterates that brand disambiguates shared codes, but it does not provide meaning beyond what the schema already contains.

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 a specific verb and resource ('Cross-reference a carbide insert grade across manufacturers') and clearly distinguishes it from sibling tools: it deals with carbide grades and ISO 513 positions, while material_cross_reference targets materials and speeds_feeds_starting_values targets starting values.

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?

It gives clear context for when to use the tool ('Given any maker's grade... returns its ISO 513 application position(s) and the grades other manufacturers publish'), with examples. However, it does not explicitly name sibling tools or state when to prefer one over the other, so it stops short of full exclusion guidance.

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?

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the curated scope (77-material set), the output composition (ISO 513 group, machining note, equivalence type), and a limitation/caveat (always verify against certificate). This gives the agent realistic expectations about coverage and reliability, though it doesn't address edge cases like no-match behavior.

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?

Four sentences, each contributing value: the core function with an example, the output details, and a safety caveat. The description is front-loaded with the main purpose and avoids redundant phrasing. It could be slightly more structured around when-to-use, but overall it's appropriately sized 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?

For a simple single-parameter tool without an output schema, the description covers the essential ground: input formats, output fields, the scope of the dataset, and a verification caveat. It doesn't mention what happens if a designation isn't found or how many matches may be returned, but the level of detail is adequate for an agent to invoke the tool correctly and interpret 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?

The input schema already provides rich detail for the sole parameter, listing all accepted formats (EN, Werkstoffnummer, AISI/UNS, JIS, common names) with examples. The tool description adds an example mapping and mentions the standards, but mostly reinforces schema content. Since schema coverage is 100%, a baseline of 3 is appropriate and the description doesn't need to compensate.

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's function: cross-referencing workpiece material designations across named standards (EN, Werkstoffnummer, AISI/ASTM/UNS, JIS). The verb 'cross-reference' with a specific resource and a concrete example make the purpose unambiguous. However, it doesn't explicitly distinguish this tool from the sibling grade_cross_reference, so it misses the active differentiation that would earn 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?

The description makes it clear that the tool accepts material designations and returns cross-standard matches, which implies the usage context. It also warns to verify against material certificates, offering practical guidance. Yet it never states when to prefer this tool over grade_cross_reference or what conditions would make the sibling more appropriate, so guidance is implied rather than explicit.

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?

With no annotations provided, the description carries the behavioral disclosure burden. It explains that the ranges are approximate practice ranges, not catalog data, and that exact-grade data takes precedence. This is useful context for interpreting results.

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 sentences with no filler. The main content is front-loaded, and the caveat about exact-grade data is included without bloating the description.

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 simple one-parameter lookup with no output schema, the description is mostly complete: it states input scope, material classes, and the approximate nature of the data. The only minor gap is that units and the exact return structure of the ranges are not specified.

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 the baseline is 3. The description adds value by expanding each ISO group into its material type (e.g., M stainless, N aluminium) and by clarifying S_TI and S_NI, which goes beyond the schema's brief enum description.

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 identifies the resource: starting cutting-speed and feed ranges for coated-carbide turning by ISO 513 material group. It does not use an explicit verb like 'get' or 'return', but the scope is specific and distinct from the sibling cross-reference tools.

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 when to use the tool by labeling the values as 'starting' and 'deliberately wide practice ranges', and it warns that exact-grade maker data wins. However, it does not explicitly name sibling tools or state when to prefer them.

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