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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses parameter constraints (title 10-200 chars, description min 20), optional fields, defaults (safety_classification default class_c), and return value (success message with ID). It does not specify error behavior for duplicate IDs or permission requirements, but covers the essential creation 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?

The description is well-structured with a one-line summary, Args list, Returns line, and an example. Every section adds necessary information without redundancy. It is efficiently organized and front-loaded with purpose.

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 description covers all nine parameters, includes a concrete example, and states the return value. Though it doesn't enumerate error scenarios, the presence of an output schema (not shown) and the comprehensive parameter documentation make it complete enough for a create 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?

Schema description coverage is 0%, but the description's Args section provides meanings, valid enums, constraints, and default for every parameter. The example demonstrates realistic usage. This fully compensates for the schema's lack of descriptions, adding significant semantic value.

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 opens with 'Create a new software requirement', which uses a specific verb and resource, and specifies the IEC 62304 Section 5.2.2 standard. This clearly differentiates it from sibling tools like update_requirement and get_requirement by defining its distinct creation role.

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 clearly states this is for creating a new requirement, which implies its use case. However, it does not explicitly exclude alternatives or mention update_requirement for modifications, so it provides clear context but no explicit when-not-to-use 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 must carry the full burden. It states the tool creates a risk control and returns a success message with a calculated risk level, which gives useful behavioral context. However, it does not disclose prerequisites (e.g., requirement existence), authorization needs, or side effects beyond creation, leaving room for more 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 well-structured with a clear purpose, an Args list, and a Returns section. Every line adds value, avoids redundancy, and front-loads the core function. It is appropriately sized for the tool's complexity.

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 description is sufficiently complete for a creation tool with an output schema. It provides an overview of inputs, the return format, and the ISO 14971 context. It could optionally mention that requirement_id is optional and what happens if omitted, but this is a minor gap given the moderate 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 description coverage is 0%, so the description fully compensates by providing meaningful explanations for all six parameters. It lists allowed values for severity and probability, which is essential and not present in the schema. Each parameter gets a concise, useful description, going well beyond the schema's bare titles.

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+resource construction ('Create risk control') and adds the ISO 14971 integration context. This clearly distinguishes it from sibling tools that all focus on requirements and documents, making the tool's purpose unambiguous.

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 creating risk controls within an ISO 14971 framework. While it does not explicitly list alternatives or exclusions, the context is clear enough given that siblings are requirement-focused. The lack of explicit 'when to use' is a minor gap.

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 burden. It discloses that the tool creates a link and returns a success message with a link ID, and it lists allowed values for source_type, target_type, and link_type. However, it does not mention validation of source/target existence, idempotency, or any side effects beyond creation.

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 well-structured with clear sections for arguments, returns, and an example. Every part adds value, and it is not overly verbose for a tool with six parameters.

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 description provides all necessary information for an agent to invoke the tool correctly: parameter names, allowed values, return type, and an example. It lacks discussion of edge cases like duplicate links or error handling, but for a creation tool this is a minor 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 coverage is 0%, but the description fully compensates by explaining each parameter with format examples (e.g., 'SWR-001') and enumerating allowed values for type and link_type. The example usage reinforces correct invocation, making semantics crystal clear.

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+resource ('Create traceability link') and immediately provides the IEC 62304 standard reference, making the tool's purpose clear and distinct from sibling tools like create_requirement or generate_traceability_matrix.

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 by defining the link creation operation and the artifact types it connects, but it does not explicitly state when to use it over alternatives or mention any exclusions. The standard reference gives context, but there is no direct 'use when' 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 present, the description carries the full burden. It mentions a return value but does not disclose whether the tool overwrites existing files, requires permissions, or the format of the generated content. These behavioral traits remain unclear.

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 and well-structured: it states the core purpose first, then lists the argument and return value. No filler or redundant content, every line 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?

For a one-parameter generation tool, the basics are covered: purpose, argument, and return value. However, missing usage alternatives and overwrite behavior leave clear gaps, making it only minimally 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?

The description explicitly explains export_path as the file path for the SRS document and provides a default value, fully compensating for the absent schema description. This gives the agent clear meaning for the parameter.

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 Software Requirements Specification with a specific standard reference (IEC 62304 Section 5.2.6), which distinguishes it from sibling tools like generate_traceability_matrix or requirement CRUD operations.

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 guidance is provided about when to use this tool versus alternatives. The description only defines what it does, not when it should be invoked, leaving the agent without explicit decision-making information.

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?

There are no annotations, and the description does not disclose side effects. It implies creation of a CSV file via export_path, but it does not state that the tool reads existing requirements/links, writes to disk, or overwrites files. The 'Returns' section only describes the success message, not behavioral implications like mutation or dependencies. This lack of transparency leaves the agent uncertain about the operational consequences.

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 extremely concise and well-structured, with a clear one-line purpose, an Args section, and a Returns section. Every word adds value, and the output format is immediately scannable. No filler or redundancy exists.

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 is simple, but the description leaves out important operational context: it does not state that the matrix is generated from existing requirements/links, nor does it explicitly mention that a file will be created (a side effect). The return value is covered, but the prerequisites and data dependencies are missing. Given the presence of an output schema, the return is adequately addressed, but overall the description is not fully complete for an agent to use it safely without additional assumptions.

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 only parameter, export_path, is briefly explained in the Args section as 'File path for CSV export' with a default. This adds meaning beyond the schema's bare property definition, clarifying the file format (CSV) and the purpose. While simple, the description sufficiently compensates for the lack of schema descriptions, though it omits details like path handling (relative vs absolute, directory creation) which would require a higher score.

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: generating a complete traceability matrix, with a specific reference to IEC 62304 Section 5.1.1. The verb 'generate' and resource 'traceability matrix' make the intent unambiguous, and it is distinct from sibling tools like generate_srs_document or create_traceability_link.

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 provides no explicit guidance on when to use this tool versus alternatives. It does not mention any prerequisites (e.g., existing requirements or traceability links) or situations where one would prefer this over other tools such as generate_srs_document. The reference to IEC 62304 implies a compliance context but does not serve as clear usage direction.

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 are provided, so the description must disclose behavioral traits. It mentions the output format but does not explicitly state that the operation is read-only, has no side effects, or any permissions requirements. The 'Get' verb implies a read, but this is not explicitly disclosed.

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 succinct, immediately states the purpose, and includes a brief 'Returns' section. Every sentence adds value and there is no redundancy or filler.

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 no-parameter statistics tool, the description provides enough information about the output. It does not mention any limitations (e.g., scope, freshness of data), but given the tool's simplicity, this is acceptable. The presence of an output schema also reduces the need to describe return values in detail.

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 has zero parameters, so schema coverage is 100% vacuously and baseline is 4. The description adds no parameter information because there are none to describe. It correctly implies the tool requires no arguments.

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 with a specific verb ('Get') and resource ('requirements dashboard statistics'). The 'Returns' line elaborates on the output, making it distinct from sibling tools like get_requirement or generate_traceability_matrix.

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 when dashboard statistics are needed, but it provides no explicit guidance on when to choose this over alternatives such as generate_traceability_matrix or search_requirements. There are no stated exclusions or preferred contexts.

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. It discloses the return format ('Formatted requirement details including traceability links') and the non-mutating verb 'Retrieve' implies read-only behavior. However, it does not disclose error handling, permissions, or explicit side-effect confirmation.

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 exceptionally concise with a clean structure: a one-line purpose, an Args block explaining the parameter, and a Returns block. Every sentence contributes 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?

For a simple parameterless-by-schema tool with an output schema, the description sufficiently covers what the tool does and what it returns. It could be improved with a note about edge cases or alternatives, but given low complexity, it is adequate.

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 schema provides no description for req_id, but the description adds 'Requirement ID (e.g., SWR-001)', giving context and an example. This meaningfully compensates for the schema's lack of parameter 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 states 'Retrieve a requirement by ID', specifying the exact operation and resource. It distinguishes from siblings like create_requirement, update_requirement, and get_requirement_history, which involve different actions or scopes.

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 direct ID lookup but never explicitly says when to use this vs. alternatives like search_requirements. No exclusions or alternative recommendations are provided, so the guideline is minimal.

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 are provided, so the description must carry the behavioral disclosure burden. It states 'Get' and 'Returns', implying a read-only operation, but does not explicitly confirm no side effects, required permissions, or any other behavioral traits. The standard reference adds context but not operational 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 brief and front-loaded with the purpose, followed by a clear Args/Returns structure. Every line earns its place without unnecessary 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?

The tool is simple with one parameter and an output schema, so the description doesn't need to detail return values. However, it lacks usage guidance and behavioral safety disclosure, which are gaps for full completeness.

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 schema provides only a title 'Req Id', while the description explains 'req_id: Requirement ID', adding semantic meaning. This compensates for the 0% schema coverage, though it doesn't specify format or examples.

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 'Get complete version history' with a specific verb and resource, and the IEC 62304 reference adds concrete context. It is distinct from siblings like get_requirement and search_requirements, which focus on current state or queries.

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 use when version history is needed, but does not explicitly state when to prefer this over alternatives or exclude other tools. No sibling comparisons are given, leaving the reader to infer 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?

With no annotations, the description carries the burden of behavioral disclosure. It states that it returns a list of matching requirements and lists valid filter values, but does not mention behavior such as combining filters (AND vs OR), handling of empty filters, pagination, or ordering. The read-only nature is implied by 'search' but not explicit.

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 and well-structured: a one-line summary, a bulleted Args list, and a Returns line. Every sentence earns its place with no redundant information. The layout is easy to scan.

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 read-only search tool with 4 optional parameters, the description covers the purpose and all parameter semantics. It lacks details on edge cases like empty filters or result ordering, but since an output schema exists, return value details are likely covered there. The description is nearly 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?

The input schema provides only names and types with zero description coverage. The description compensates by enumerating valid values for status, category, and safety_class, and clarifies that search_text searches title and description. This adds significant semantic meaning 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 states 'Search and filter requirements' which is a specific verb+resource combination. It distinguishes from siblings like get_requirement (which likely retrieves a single requirement) by focusing on search and filtering. The Args list further clarifies the scope.

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 searching and filtering requirements but does not explicitly mention when to use this tool versus alternatives like get_requirement. There is no 'when-to-use' or 'when-not-to-use' guidance, leaving the context to be inferred from the function name and sibling names.

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 must disclose behavior on its own. It does so by mentioning version control, the mandatory change_reason for audit, and that a new version number is returned. It does not spell out every side effect, but it covers the most important behavioral traits for a mutation tool in a regulated environment.

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 well-structured: a one-sentence purpose, a compact Args list with clear per-parameter semantics, and a Returns line. No redundant information or fluff; every sentence adds value.

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 7-parameter mutation tool with no annotations, the description provides complete context: the update purpose, version control, audit rationale, all parameter meanings, allowed values, and the return type. The presence of an output schema is not necessary because the Returns line covers the outcome.

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 is the only source of parameter meaning. It lists all 7 parameters with explicit explanations, marks required ones, and even enumerates allowed values for status and priority. This fully compensates for the sparse 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 opens with 'Update requirement with version control (IEC 62304 Section 8)', which clearly identifies the verb (update), the resource (requirement), and a key differentiator (version control/IEC 62304). This distinguishes it from siblings like create_requirement, get_requirement, and get_requirement_history.

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 states the purpose and introduces an audit requirement ('change_reason: Reason for the change (required for audit)'), indicating when this tool should be used in a regulated workflow. It does not explicitly name alternatives or exclusions, but the context is clear enough to guide appropriate use.

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