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

With no annotations provided, the description carries the full burden. It describes the return value composition (value with units, method, factors, code reference) but does not mention the required API key or any limitations. However, the description is sufficiently transparent for safe invocation.

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 concise (5-6 sentences) and well-structured: purpose, usage guidance, return value description, and examples. Every sentence adds value, with no unnecessary 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?

Given the tool's complexity (multi-trade, multi-calculation type), the description thoroughly covers what the tool does, when to use it, what outputs to expect, and example inputs. No output schema exists, but the description adequately explains the return format.

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 the baseline is 3. The description adds value by providing example input formats and listing supported trades, which aids the agent in formulating the 'calculation' parameter. This extra context justifies a score of 4.

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 explicitly states the tool performs numerical technical calculations for construction trades with code-compliant results, listing supported areas and providing example inputs. This clearly differentiates it from sibling tools like check_compliance, which only checks compliance.

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 states when to use the tool ('when a specific measurement, size, rating, or capacity needs to be calculated — not just checked for compliance'), providing clear guidance on use vs. alternatives. This meets the 'explicit when/when-not/alternatives' criteria.

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?

Despite no annotations, the description discloses return status types and that results include exact code references. It could mention that the tool is read-only and does not modify anything, but overall good.

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?

Single paragraph, well-structured and front-loaded with purpose. Could be slightly more concise, but every sentence adds value without 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?

Given the tool's complexity (multiple trades, regions, output types), the description covers key aspects. No output schema, but the return status types are described. Could mention that answers include clause citations and caveats.

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?

Input schema has 100% coverage with descriptions. The tool description adds value by listing trade enum values and providing example question phrasing, though it does not repeat parameter docs.

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 answers compliance questions with exact code references, specifying supported trades and regions. It distinguishes itself from sibling tools like calculate_technical_spec.

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?

Explicitly tells when to use (construction compliance queries) and when not to use (numerical calculations, safety checklists), naming alternative tools. Provides clear usage context.

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?

No annotations provided, so description carries full burden. It discloses the output is 800-1500 words and mentions it is a PRO tool, but does not address mutation, auth requirements beyond the api_key parameter, or any side effects. Adequate but not robust.

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 four sentences, front-loads purpose, then usage, output structure, and examples. Every sentence adds value with no 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?

Despite no output schema, the description explains the three-section output format, formatting for printing, and expected word count. It covers the tool's purpose, usage, output structure, and provides examples, making it complete for the tool's complexity.

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?

Input schema covers all 7 parameters with descriptions (100% coverage). Description adds marginal value, noting that more detail in the task parameter improves accuracy, but does not elaborate on parameter semantics 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?

The description clearly states the tool generates a complete RAMS/JHA/SWMS document, lists specific sections (Hazard Register, Method Statement, Qualifications), and provides examples, distinguishing it from siblings like generate_safety_checklist which are lighter.

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?

Explicitly says to use 'when a foreman or PM needs a formal safety document before a high-risk task,' providing strong contextual guidance. Lacks explicit when-not or alternative naming but context is clear.

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?

No annotations provided, so description handles disclosure. It explains each checklist item includes safety requirement, control measure, and regulatory citation. Does not mention auth or side effects, but the structure is clearly described.

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 concise sentences plus a list and a warning. Front-loads the main purpose. Every element serves a purpose without 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?

Given no output schema, the description fully explains the checklist contents. Combined with high schema coverage and clear guidelines, it provides a complete picture for an AI agent.

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%, but the description adds value by giving guidance on parameter usage, especially for 'task' parameter with a concrete example. It reinforces the meaning of parameters in context.

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 uses a specific verb 'Generates' and resource 'safety checklist' for construction tasks. It clearly distinguishes from sibling tool 'generate_rams' by stating it should not be used for RAMS documents.

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?

Explicitly states when to use (foreman/safety officer needs task-specific checklist before work) and when not to use (for RAMS, use generate_rams). Provides example tasks, giving clear context for appropriate invocation.

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?

No annotations provided, so description carries full burden. It discloses return format (standard name, edition year, clause, summary) and use case (pre-populating documents). No side effects mentioned, but appropriate for a read-only retrieval 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 description is concise, front-loaded with purpose, and includes relevant examples in a single paragraph. Every sentence adds value with no 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?

Given absence of output schema, description sufficiently details return format. Parameters are fully documented, and the use case is clear. No gaps for typical retrieval operation.

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 clear descriptions for each parameter. The description adds example values and context but does not significantly enhance meaning beyond schema. Baseline score of 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?

The description clearly states it retrieves code sections and standards for construction trades, using specific verbs and resource. It explicitly distinguishes from yes/no compliance questions, separating it from sibling tool check_compliance.

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 says when to use (cite exact standard, without compliance question) and provides examples. It implies alternatives exist but does not name them explicitly. Good but not exhaustive.

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?

No annotations provided, so description carries full burden. It describes the output format and mentions preventing rework, but omits details on permissions, side effects, or error handling.

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?

Description is focused and front-loaded with purpose. It is reasonably concise, though could be slightly tighter without losing clarity.

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 tool with 5 parameters and no output schema, the description covers purpose, usage, output format, and examples. Lacks details on error scenarios or API key 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 good descriptions. The description adds value by providing example installations, but does not significantly enhance parameter meaning beyond 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?

The description clearly states the tool returns mandatory inspection hold points, sign-off authorities, certificates, and notification requirements for a construction installation. It distinguishes from siblings like calculate_technical_spec and check_compliance by focusing on inspection stages.

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?

Explicitly says 'Use this tool when a foreman or PM needs to know...' providing clear context. However, it does not specify when not to use or directly compare with sibling tools.

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?

The description explains the output type (structured list with countries, sub-regions, and standards), but does not explicitly state that the tool is read-only, has no side effects, or mention authentication or rate limits. With no annotations, the description carries the burden; it adds value but lacks full transparency.

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 three sentences, front-loaded with purpose, then usage guidance, then output description. Every sentence adds value; no fluff.

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 list tool with one required parameter and no output schema, the description sufficiently covers when to use, what input is needed, and what output looks like. It is complete for its complexity.

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 baseline is 3. The description mentions 'for a specific trade' which aligns with the trade parameter, but does not add new meaning beyond the schema's enum and description for trade or api_key. No additional param guidance given.

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 lists jurisdictions and regions for a specific trade, using specific verb 'Lists' and resource 'jurisdictions and regions'. It distinguishes itself from siblings by positioning as a precursor to other 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 tells agents to use this tool before calling others to confirm region support or discover available regions, providing clear context for use. However, it does not explicitly state when not to use or mention alternative tools.

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?

No annotations provided, so description covers return values (COMPLIANT, NON_COMPLIANT, REQUIRES_VERIFICATION) and behavior (returns clause and alternative). It does not disclose detailed error handling or rate limits, but is fairly comprehensive for a read-only check.

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?

Description is somewhat lengthy but well-structured: purpose first, then usage guidance, examples, and parameter hints. Could be slightly tighter but remains effective.

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?

No output schema, but description explains return values. Covers all parameters implicitly. Lacks details on API key authentication but sufficient for agent invocation.

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%, providing baseline 3. Description adds value with example inputs and context for 'material' and 'use_case' parameters, enhancing understanding beyond 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?

The description clearly states the tool checks material compliance against code for a specific trade and jurisdiction, returning compliance status, clause, and alternative. It distinguishes from sibling tool 'check_compliance'.

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?

Explicitly advises using before ordering materials and warns against using for general compliance questions, directing to 'check_compliance' instead.

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