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

No annotations provided. Description claims 'list every test case' but input schema includes an optional `limit` parameter (default 10, max 100), implying pagination and a cap, creating a contradiction. No mention of ordering, error handling, or behavior when no 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?

Single sentence is concise and front-loaded with the core action. However, could include more details without becoming verbose; still 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?

Given 4 parameters, no annotations, and 0% schema coverage, description is incomplete. Lacks prerequisites, error cases, and clarification of limit behavior. Output schema exists but does not compensate for missing behavioral context.

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%. Description does not elaborate on any parameter (guide, version, category, limit) beyond their existence. No format, default values, or constraints explained.

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?

Description clearly states verb 'List', resource 'test cases', and scope 'in one guide/version/category'. It distinguishes from siblings like guide_search (search) and guide_list_tests (likely broader).

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 on when to use this tool vs alternatives such as guide_search or guide_list_tests. No mention of prerequisites or typical use cases.

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 full burden but only states the action. It does not disclose whether the tool is read-only, requires specific permissions, has rate limits, or what side effects (if any) occur. The description is purely functional without behavioral context.

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 a single concise sentence that efficiently conveys the core function. However, it could be improved by structuring the explanation to explicitly mention the key parameters (guide, canonical_id, version_a, version_b) for 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?

Given the 4 parameters, no annotations, and presence of an output schema (which reduces the need to describe return values), the description still fails to provide essential context like what constitutes a 'guide' or how versions are specified. The tool is underspecified for reliable agent use.

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%, yet the description does not elaborate on any parameter meanings. It implies the parameters correspond to a test case and two versions but omits details like expected formats or relationships. The agent must infer parameter semantics solely from names, which is insufficient for correct invocation.

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 specifies a clear verb 'Compare' and a specific resource: 'test case's title/objectives/sections/source across two compiled guide versions'. It uniquely identifies a comparison operation, clearly distinguishing it from sibling tools like guide_search or guide_browse_category.

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 on when to use this tool versus alternatives like guide_get_test or guide_list_tests. There is no mention of prerequisites, such as needing to identify a test case's canonical_id or versions beforehand, which limits the agent's ability to decide appropriately.

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 must convey all behavioral traits. It mentions it 'explains' but does not state whether it's read-only, has side effects, or requires specific permissions. Minimal disclosure beyond output fields.

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 sentence, but it is front-loaded with the purpose. Could be more concise by removing redundant listing of fields, but overall acceptable.

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?

Output schema exists but description fails to clarify how to specify the relationship (by IDs vs relationship_id). For a tool with three optional input fields, more detail is needed to avoid ambiguity.

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%, and description lists 'source test, target test, type, and full provenance' as outputs, not inputs. The actual parameters (source_test_id, target_test_id, relationship_id) are not explained, and their purpose is unclear from the 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 the tool explains a relationship edge and lists the provenance fields it provides. It distinguishes from siblings by focusing on a single relationship rather than listing or searching, though not explicit.

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 on when to use this tool vs alternatives like guide_get_related_tests or guide_find_by_feature. No exclusions or prerequisites 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?

No annotations are provided, so the description carries full burden. It discloses OR semantics and matched_terms but omits behavioral traits like authentication needs, read-only nature, rate limits, or failure modes. This is insufficient 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?

Single sentence, front-loaded with key semantics and examples, no filler. 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?

Has output schema to explain return values, but description lacks edge cases (e.g., no matches) and parameter constraints. Adequate for a simple search but not comprehensive.

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%, and the description adds no per-parameter details beyond field names. Parameters like limit and guides remain unexplained, forcing the agent to rely on names and types alone.

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?

Description clearly states the tool finds test cases by feature keywords with OR semantics, provides examples (e.g., oauth, webview), and mentions result structure. This distinguishes it from sibling tools like guide_search or guide_browse_category.

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 context (search with OR semantics) but does not explicitly state when not to use or suggest alternatives. For a feature-driven search, this is sufficient for an agent to infer appropriate use.

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 full burden. It discloses that LLM-inferred edges are excluded unless include_inferred is true, which is a key behavioral trait. However, it lacks details on performance, error handling, or what happens if the test_id does not exist.

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 a single sentence that directly states the purpose. It is concise and front-loaded, though it could benefit from slightly more structure to improve readability.

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 having an output schema, the description is very brief and does not cover important context such as error cases, performance implications, or the nature of 'curated relationships'. More detail would help the agent use the tool effectively in complex scenarios.

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. It explains the include_inferred parameter's default and behavior, but provides no additional meaning for test_id, max_depth, or relationship_types beyond their schema constraints.

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 ('Traverse') and resource ('curated relationships from a test case'), clearly indicating the tool's function. However, it does not distinguish this tool from siblings like guide_explain_relationship or guide_get_test, which could cause confusion when selecting the appropriate tool.

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 guidance is provided on when to use this tool versus alternatives. The mention of include_inferred defaulting to false offers a subtle usage hint, but there is no context about prerequisites, when not to use, or recommended scenarios.

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 full burden for behavioral disclosure. 'Full provenance' hints at metadata, but the description does not clarify read-only status, authentication needs, or side effects. The tool is likely read-only, but this is not stated.

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 a single 15-word sentence, front-loaded with the key action and resource. It is concise and efficient, though this brevity omits important details covered in other dimensions.

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 has an output schema (not shown) which reduces the need to describe returns, but with no annotations and no parameter descriptions, the description falls short. It provides minimal context for correct invocation, lacking usage guidance and behavioral details.

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%, and the description does not mention either parameter (test_id or section). The optional enum for section is not explained, nor is the required test_id. The description adds no value beyond what the schema 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?

The description explicitly states the action ('Fetch'), the resource ('raw text of a section for a test case'), and the scope ('single section or all sections') with an additional qualifier ('full provenance'). It clearly differentiates from sibling tools like guide_get_test which likely returns structured test data.

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 retrieving raw text of a test case section, but it does not provide explicit guidance on when to use this tool versus alternatives like guide_get_test or guide_search. No exclusion criteria or context is given.

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 carries full burden. It does not disclose whether the operation is read-only, requires authentication, error handling (e.g., not found), or side effects. The boolean flags that affect behavior are not mentioned.

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 sentence with no redundant words, front-loaded with the core action and resource. Every word serves a 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?

Despite having an output schema and multiple parameters, the description only covers the identifier aspect. It omits details about optional flags, expected output, and error conditions, making it insufficient for complete understanding.

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 adds meaning to test_id by listing allowed identifier types, but does not explain the three boolean parameters (include_inferred, include_full_content, include_relationships). With 0% schema description coverage, the description should compensate for all parameters, but it only partially addresses one.

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?

Description clearly states verb 'Fetch' and resource 'one test case', and specifies multiple identifier types (versioned id, canonical id, alias, slug). This distinguishes it from sibling tools like guide_list_tests (list) and guide_search (search).

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?

Implicitly tells when to use: when you have one of the specified identifiers and need a single test case. No explicit exclusions or alternatives are mentioned, but the context with siblings is clear given the specific identification methods.

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 mentions pagination via cursor as offset, which is useful. However, it does not disclose read-only nature, rate limits, or any side effects. The output schema exists but behavior beyond pagination is 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 extremely concise at two sentences (18 words), with no unnecessary information. It is front-loaded 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?

Given the tool has 5 parameters with no schema descriptions and no annotations, the description is insufficient. It omits details on required guide, limit range, and version parameter, leaving the agent guessing. The output schema exists but does not compensate for missing parameter guidance.

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%. The description only explains cursor and mentions category filtering, but fails to describe guide, limit, and version parameters. It adds minimal meaning beyond the schema structure.

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 test cases in a guide/version, with optional category filtering. It is specific about the resource and action, but does not explicitly differentiate from sibling tools like guide_get_related_tests.

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 guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. It only describes a basic usage hint about cursor.

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 full burden. It discloses that the output is unexecuted and unverified, and directs the agent to the 'uncertainty' field, providing useful behavioral context beyond the 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?

The description is two sentences, front-loading the purpose and immediately adding a critical caveat. Every sentence earns its place 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 the presence of an output schema and a single complex parameter, the description is moderately complete but lacks detail on what 'candidates' means, how to interpret the output, and the role of optional parameters like guides or include_inferred_relationships.

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 has 0% schema coverage and does not explain any parameter beyond mentioning the target system profile. The input schema is relatively self-explanatory, but the description fails to add value for the nested objects like guides or include_inferred_relationships.

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 produces candidate tests for a target system profile, using a specific verb and resource. While it distinguishes the tool's purpose from siblings like guide_list_tests, it could explicitly differentiate from guide_get_related_tests.

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 context by stating the output is not a verified pentest plan and nothing has been executed, but it does not explicitly state when to use this tool over alternatives or provide 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?

No annotations provided, so description carries full burden. It states search modes but does not disclose behavioral traits like result ranking, pagination, or whether filters are exact or fuzzy. Lacks details that would help an agent understand the tool's 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?

Single sentence, front-loaded with key information (search, guides, modes). Every word earns its place; no unnecessary text.

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 output schema existing, the description is too brief for a complex tool with multiple search modes and optional filters. It fails to mention paging, result structure, or how filters interact. Incomplete given 0% parameter descriptions and lack of 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 description coverage is 0%; description adds meaning by explaining search_mode via the four modes listed. However, other parameters like limit, guides, platforms, categories are not explained beyond their schema titles and constraints. Baseline 3 with partial compensation.

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 verb 'Search' and the resource 'OWASP testing guides', and specifies the search modes (exact id, full-text, semantic, hybrid), making it distinct from sibling tools like guide_get_test or guide_list_tests.

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 guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or when not to use it. The description only implies usage for searching across guides.

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 carries full burden. It discloses that the tool checks existence and hash matching but does not mention side effects, auth needs, or error behavior. With an output schema, return values are covered, but further behavioral context would help.

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 a single sentence that is front-loaded with the core action. No extraneous words, efficiently conveying purpose and usage.

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 low parameter count and the presence of an output schema, the description covers the main purpose and usage scenario. It lacks detail on return values and errors, but these are partially addressed by the output schema.

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. It maps 'test id/version' to test_id and 'content hash' to expected_content_hash, adding meaningful context beyond the schema's bare property 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 clearly states the verb ('check') and the resources ('test id/version', 'content hash', 'compiled registry'), making it easy to distinguish from sibling tools like guide_browse_category or guide_search.

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 says 'use before trusting a previously-cached citation,' providing clear guidance on when to use. However, it does not mention when not to use or list alternatives.

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