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

With no annotations, the description must disclose behavioral traits. It only states what the tool does, without mentioning that it is read-only, potential performance implications, or any prerequisites. The description lacks transparency about side effects or limitations.

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 with two sentences. The first sentence front-loads the main purpose, and the second elaborates. It is well-structured for a brief description, though it could potentially include more details without being verbose.

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 7 parameters and no output schema, the description covers the core functionality but lacks details on the output format, return structure, or any limitations. It is adequate for a simple tool but not fully comprehensive for the 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 'bugs, CVEs, and recommendations' which aligns with parameters, but does not add significant meaning beyond the schema descriptions. No extra clarification or context added for parameters.

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 compares two software versions on bugs, CVEs, and recommendations. It uses a specific verb 'compare' and identifies the resources. However, it does not explicitly distinguish from sibling tools like comprehensive_analysis, but it is clearly a comparison 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 guidance is provided on when to use this tool versus alternatives. The description does not specify prerequisites, exclusions, or context where this tool is preferred over siblings like smart_search_strategy or multi_severity_search.

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 the full burden. It discloses that the tool combines bug database search and web search guidance, implying multi-step behavior. However, it does not describe side effects (none expected), authorization needs, rate limits, or response size. For a complex analysis tool, more behavioral context would be beneficial.

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-loaded with a bold-purpose statement ('BEST FOR DETAILED ANALYSIS'). Every clause adds value without redundancy. It efficiently conveys the tool's purpose, outputs, and ideal use cases.

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 (combined searches, recommendations) and lack of output schema, the description covers key aspects but lacks details like output format, processing time, or result granularity. It is adequate but would benefit from a sentence about expected response structure.

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 description adds some value by contextualizing parameters (e.g., 'include_web_search_guidance' maps to 'web search guidance'). However, it does not explain enum values for analysis_focus or version format beyond what the schema provides. The added context is moderate.

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 provides comprehensive product analysis by combining bug database search with web search guidance for EoL information. It explicitly mentions outputs: known issues, lifecycle status, and actionable recommendations. This differentiates it from narrower sibling tools like search_bugs_by_keyword or compare_software_versions.

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 it's 'best for detailed analysis' and 'ideal for failover issues, configuration problems, and product reliability concerns,' giving clear usage guidance. However, it does not explicitly state when not to use it or provide alternatives, which would be helpful given the large number of 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?

No annotations are provided, so the description must convey behavioral traits. It only states 'get details' and the limit of 5 IDs, without disclosing whether the operation is read-only, rate limits, or what 'details' includes. This is insufficient for a tool with no annotation support.

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, efficient sentence. It is front-loaded and contains no fluff. However, some might argue it is under-specified, but it is concise and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description is minimally adequate. It states the core functionality but lacks context on return format, error handling, or behavior when IDs are invalid. It could be more 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?

With 100% schema description coverage for a single parameter, the baseline is 3. The description adds 'up to 5', which is already present in the schema's parameter description, so no significant additional 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 clearly states the tool's function: retrieving details for specific bug IDs. It uses a specific verb 'Get details' and resource 'bug IDs', and the sibling tools are primarily search-based, making this tool distinct as a direct retrieval by ID.

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 you have specific bug IDs but provides no explicit guidance on when not to use it or what alternatives exist. The context of sibling search tools suggests differentiation, but the description lacks explicit usage boundaries.

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 full burden. It does not disclose safety information (read-only implied but not explicit), rate limits, authentication requirements, or data freshness. The description only states that it 'returns comprehensive case information,' which is insufficient.

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-loaded with the verb and resource, and contains no extraneous words. Every sentence contributes 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?

The tool has a single simple parameter and no output schema. The description lists some return fields but does not provide a complete picture of what to expect. Given the number of siblings, more differentiation and detail would improve 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?

Schema coverage is 100%; the parameter case_id is fully described in the schema. The tool description adds no new meaning beyond summarizing the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's action ('Get detailed information') and resource ('single case ID'), and lists returned fields (status, severity, etc.). However, it does not distinguish itself from siblings like get_case_summary or get_bug_details.

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 such as get_case_summary or search_cases_by_*. The description does not mention exclusions or prerequisites.

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 full transparency burden. It only states 'Returns brief information' without disclosing what fields are included, whether authentication is required, rate limits, or any side effects. This significant gap leaves the agent uninformed about critical behavioral traits.

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 consists of two clear, front-loaded sentences with zero extraneous information. Every word contributes to conveying the tool's function and constraint.

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 absence of an output schema, the description should elaborate on what 'brief information' includes. It does not, leaving the agent uncertain about the return format. However, the core functionality and constraints (max 30 IDs) are conveyed, so completeness is adequate but not thorough.

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 describes both parameters with 100% coverage, including the max count for case_ids and enumeration for sort_by. The description adds no additional semantic value beyond the tool's purpose, warranting the baseline score of 3.

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 'Get', the resource 'case summary information', and the scope 'up to 30 specific case IDs' for multiple cases. This distinguishes it from siblings like 'get_case_details' which presumably returns full details for a single case.

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 obtaining summaries of multiple cases by ID, but does not explicitly state when to use this tool versus alternatives (e.g., get_case_details for full details, search_cases_by_user for user-based queries). No exclusions or when-not guidance is provided.

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 should fully convey behavior. It only restates the capacity constraint (up to 75 serials) already present in the schema and lists output fields, but omits safety aspects, error handling, or read-only semantics.

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 with no redundant words. Front-loaded with action and capacity, then lists return contents. Every sentence 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?

Given high schema coverage and only two parameters, the description is adequate but lacks usage guidelines and behavioral details. The output specification is partial but reasonable for a coverage-status 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 coverage is 100% with good descriptions for both parameters. The description adds minimal value beyond the schema, only reinforcing the max 75 serial numbers. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves detailed coverage status, warranty, and product information for up to 75 serial numbers. It distinguishes itself from the sibling 'get_coverage_summary_by_serial' by implying it returns more comprehensive data, though not explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like get_coverage_summary_by_serial, nor does it mention any prerequisites or context-specific conditions.

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 only states that the tool returns coverage information, without disclosing side effects (none expected, but not stated), authentication needs, rate limits, or any behavioral constraints. The description lacks critical safety/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?

Two sentences, front-loaded with the action, no fluff. Every sentence 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?

The description is adequate for a simple lookup but lacks details on return format (no output schema) and pagination behavior. Given the schema covers parameters well, but the tool's full context (e.g., what coverage summary includes) is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with descriptions for both parameters. The description adds context that instance numbers are unique identifiers in Cisco systems, but does not elaborate on page_index (pagination). Overall, the description adds marginal value 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 action ('Get coverage summary') and the resource ('by instance numbers'), differentiating from siblings like 'get_coverage_summary_by_serial' and 'get_coverage_status_by_serial'. It also explains what instance numbers are.

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 instance numbers are available, but does not explicitly state when to use this tool versus alternatives (e.g., by_serial). No 'when not to use' or alternative tool names are mentioned.

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 read behavior and returns 'brief coverage status and key dates' but lacks details on output format, authentication, or side effects. Adequate but not rich.

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 with no redundancy. The first sentence states the core function and limit, the second clarifies purpose. Every word 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?

Given no output schema, the description vaguely outlines the return type ('brief coverage status and key dates'). It addresses the input limit and quick-lookup context. While more detail on output or differentiation from sibling tools would improve completeness, it is sufficient for a simple 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 coverage is 100%, so baseline is 3. The description reinforces the 75 serial number limit but does not add new semantic information beyond the schema descriptions for 'serial_numbers' and 'page_index'.

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: 'Get summary coverage information for up to 75 serial numbers' with output specifics. It distinguishes from siblings like 'get_coverage_summary_by_instance' by specifying serial numbers as input and from 'get_coverage_status_by_serial' by implying summary vs. status.

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 this for quick coverage lookups without full details', providing when-to-use guidance. It implies not for full detail lookups but does not name alternatives or exclusions directly.

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 fully discloses behaviors: automatic multi-severity search, result combination, severity breakdown counts, and automatic fallback from product_id to keyword search. This adds significant value 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 concise, with two clear sentences for main functionality and a separate SMART FALLBACK explanation. No redundant information; 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?

Given 4 parameters, 100% schema coverage, no output schema, and many sibling tools, the description adequately covers usage, behavior, and fallback. It is complete for an AI agent to invoke correctly.

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 further context, e.g., version auto-inclusion in keyword search, and search_type guidance for product_series vs product_id. This enriches parameter understanding.

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 purpose: automatically searches multiple severity levels and combines results with breakdown counts. It uses strong action verbs and distinguishes itself from sibling tools by addressing the API limitation that requires separate calls per severity.

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 you need severity 3 or higher' or any range) and provides a 'SMART FALLBACK' behavior. However, it does not directly compare to sibling tools or state when not to use it.

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 the full burden of behavioral disclosure. It only states the core function but omits details like error handling (e.g., unknown product ID), required permissions, or whether the search strategies are returned as text or structured data.

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 deliver the purpose and value without extraneous information. Every word earns its place, and the description is front-loaded.

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 tool with 2 parameters and no output schema, the description is adequate but lacks error behavior and typical use-case context. It could mention that product IDs follow Cisco patterns or that the tool expects exact IDs.

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 adds context by mentioning 'web search strategies,' which relates to the include_search_strategies parameter. However, it does not elaborate on the format or content of the strategies.

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 'resolves' and the resources: product IDs to full product names and web search strategies. It distinguishes from sibling tools like search_bugs_by_product_id by focusing on name resolution rather than bug 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 implies usage when converting product IDs to names, but does not explicitly state when or when not to use it, nor mention alternatives among siblings. Example: 'Helps convert technical product codes to searchable terms' suggests a pre-processing step for other 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?

With no annotations, the description carries full burden. It reveals that the tool normalizes versions and product IDs and broadens search scope. However, it does not detail the exact algorithm, failure behavior, or how far broadening goes.

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, no wasted words. Front-loaded with the core behavior and key differentiators.

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 complexity and no output schema, the description provides a high-level overview but lacks details on return format, error handling, and the precise broadening strategy, leaving some gaps.

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%, baseline 3. The description adds slight value by stating that severity_range is searched level by level and version is normalized, but most parameter meaning is in 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's purpose: it automatically tries multiple search strategies, starting specific and broadening scope. It highlights key features like version normalization and product ID variations, which distinguish it from sibling tools that require exact matches.

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 scenarios where automatic broadening is desired but lacks explicit guidance on when not to use this tool or which sibling tools might be more appropriate for specific needs.

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, but description discloses key behaviors: severity returns exact match only, status limited to one value, keyword cannot be product ID. Missing details on default sort, pagination, or read-only nature, but still strong.

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?

Three concise sentences with purpose and key usage notes front-loaded. 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?

No output schema, description doesn't explain return format. But given 6 params and sibling tools, the description covers core aspects adequately. 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 covers all parameters, but description adds extra context: severity exact match, status single value, keyword not for product IDs. Adds value 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 searches for bugs using keywords in descriptions and headlines. It also distinguishes from siblings by specifying when to use alternative tools for product IDs or severity ranges.

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 (general terms, symptoms) and when not (product IDs, severity ranges). Names alternative tools: search_bugs_by_product_id and multi_severity_search.

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 exist, so the description carries the full burden. It discloses that the API supports up to 75 versions in one call and warns against misuse. It does not cover auth or rate limits, but the key behavioral trait is well communicated.

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 paragraphs with front-loaded purpose and critical usage note. Every sentence adds value, 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 7 parameters, no output schema, and no annotations, the description covers main functionality, constraints, and alternatives. It explains pagination only implicitly (page_index in schema) but is otherwise thorough for a search 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 coverage is 100%, baseline is 3. The description adds value by explaining the software_releases parameter's comma-separated format and 75 version limit, and clarifies the severity parameter's single-value constraint and alternative tool for range searches.

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 searches bugs by specific product ID and software releases. It distinguishes from sibling tools by mentioning search_bugs_by_product_series_affected for product series searches.

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 this tool (exact product ID and software versions), warns against making multiple separate calls, and provides an alternative for product series searches.

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 bears full responsibility for behavioral disclosure. The description does not mention side effects, authentication needs, rate limits, or data scope. It only states the search operation without additional behavioral context, leaving significant gaps for an unannotated 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 brief and entirely relevant: two sentences conveying purpose and when to use. No extraneous information; every sentence 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?

Despite having 6 parameters and no output schema, the description does not explain return values or behavioral constraints. It lacks context on pagination, filtering behavior, and result structure, which is needed given the tool's complexity and missing 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 100%, so the input schema already documents all 6 parameters with descriptions. The tool description adds no new parameter semantics beyond what the schema provides. 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 the action ('Search bugs') and the specific resource ('by specific base product ID (e.g., C9200-24P)'). It distinguishes from sibling tools like keyword search by specifying the exact product ID use case.

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 this tool ('when you have an exact Cisco product ID') and when not to ('For general product searches by name, consider using keyword search instead'), naming a concrete alternative.

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 for behavioral disclosure. While the tool's name and description imply a read-only search operation, it does not explicitly state safety or idempotency. Behavioral traits like auth requirements or rate limits are not mentioned. The parameter descriptions are detailed, but the narrative description lacks additional 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 extremely concise: two sentences that front-load the purpose and provide immediate usage guidance. Every sentence earns its place, with no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 parameters, 2 required, and no output schema, the description covers the essential aspects, and the schema descriptions are highly detailed. However, the description does not specify what the tool returns (e.g., a list of bugs with basic fields), which is a minor gap given the lack of an output schema. Overall, it is nearly 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%, so baseline is 3. The tool description adds minimal semantic value beyond the schema, mainly reiterating the product name requirement and pointing to a sibling tool. The schema descriptions themselves are thorough, covering enums, defaults, and usage notes, so the description does not significantly enhance parameter understanding.

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 'Search bugs by full product name and affected releases', specifying the verb (search) and resource (bugs) with a clear scope (by product name and affected releases). It also distinguishes from the sibling tool 'search_bugs_by_product_id', which is mentioned explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool (full descriptive product names) and when not to use it (product IDs), providing an alternative: 'Use search_bugs_by_product_id for product IDs'. Additionally, parameter descriptions for 'status' and 'severity' provide clear constraints (only one status allowed, use multi_severity_search for ranges).

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 bears full responsibility. It fails to disclose any behavioral traits such as mutation, rate limits, authentication requirements, or error handling. The only behavioral implication is the input format constraint, which is more about parameter semantics.

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: two sentences with no wasted words. It front-loads the purpose and immediately provides a critical usage note. Every sentence 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?

Given no output schema and 7 parameters, the description covers the essential purpose and key constraint but lacks details on pagination, result format, error responses, or behavior when no results are found. It is minimally adequate but not thorough.

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 adds value by explaining that product_name requires full names and fixed_releases expects comma-separated versions with examples. This is helpful but does not significantly elevate 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 'Search bugs by full product name and fixed releases.' It distinguishes from sibling tool search_bugs_by_product_id by specifying the requirement for full descriptive names, not IDs, making the purpose specific and actionable.

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 tells when to use this tool (full product names) and when to use an alternative (product IDs with search_bugs_by_product_id). It provides clear context but does not cover other potential usage scenarios or exclusions related to other siblings.

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?

Without annotations, the description carries the full burden. It discloses key constraints (no leading zeros, single status filter, exact severity filter) but does not mention authentication, rate limits, or whether the operation is read-only. Adequate but not exhaustive.

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 front-loaded with the purpose. Every sentence adds value, and the important notes are highlighted with 'IMPORTANT'. 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?

For a search tool with 7 parameters and no output schema, the description covers key aspects: what it does, required params, format guidelines, and filter limitations. It lacks output format details but the schema descriptions are 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 coverage is 100%, so the description adds value beyond the parameter descriptions with examples for product_series and affected_releases, and explicit constraints like status limitation and severity exact filter. It enriches the schema definitions.

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 specifies the action ('Search bugs') and the resource ('by product series and affected releases'). It distinguishes from sibling tools like search_bugs_by_product_name_affected by focusing on product series names and affected releases.

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 provides important usage notes such as the API version format and that only one status is allowed. However, it does not explicitly differentiate when to use this tool over similar siblings like search_bugs_by_product_name_affected.

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, but the description compensates by detailing constraints like single status limitation and version format requirements. Could add more on pagination or rate limits, but sufficient for a read-heavy search 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?

Every sentence adds value; no redundancy or fluff. Front-loaded with purpose then constraint details. Well-structured and easy to parse.

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 7 parameters, no output schema, and no annotations, the description covers the core functionality, formatting tips, and key constraints. Slight gap on result structure or example, but overall 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 coverage is 100%, but the description adds significant meaning beyond the schema, such as clarifying severity values, version format, and status usage. Enhances understanding of parameter behavior.

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 searches bugs by product series and fixed releases, using specific verbs and resources. It distinguishes from sibling tools like search_bugs_by_product_series_affected and multi_severity_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?

Explicitly explains when to use this tool (for searching by fixed releases) and when not (e.g., for severity ranges, use multi_severity_search). Provides critical formatting notes and valid input ranges.

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 exist, so the description must carry the behavioral burden. It mentions the 'max 10' constraint but omits other behaviors like pagination, sorting defaults, or date range interactions. The description is accurate but not exhaustive.

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, front-loaded with the core action and constraint. Every word 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 6 parameters and no output schema, the description is minimal. It does not explain return values or how optional filters interact, though parameter descriptions are detailed. Adequate 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 100%, so the schema already explains each parameter. The description adds no new parameter-specific information beyond the schema, meeting the baseline of 3.

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: searching for cases by specific contract IDs, with a maximum of 10. This explicitly distinguishes it from sibling tools like search_cases_by_user, which search by different criteria.

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 clear context for when to use the tool (when you have contract IDs) and mentions a key constraint (max 10). It does not explicitly list alternatives or when-not-to-use, but the sibling list allows inference.

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

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

No annotations are provided, so the description carries full burden. It only states basic purpose and a limit on user IDs, but fails to mention sorting defaults, pagination, date range constraints, status filtering, authentication requirements, or any rate limits. This is minimal behavioral disclosure for a search 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 a single sentence, which is concise but too brief. It lacks structure and does not highlight key aspects. It is not verbose, but could be more informative without adding length.

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 absence of an output schema, the description should explain what data is returned (fields, format). It does not. It also omits default behaviors (e.g., sort order, pagination page index default 5). The description is insufficient for an agent to fully understand the tool's capabilities.

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 baseline is 3. The description adds no extra semantic value beyond the schema; it only repeats the user ID limit already present in the schema. It does not clarify the meaning or interplay of parameters like date ranges or status flag.

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 purpose: 'Search for cases associated with specific user IDs (max 10). Returns cases owned by or involving the specified users.' This distinguishes it from sibling tools like search_cases_by_contract.

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 versus alternatives. The description does not mention when to choose it over other search tools, nor does it specify prerequisites or excluded 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, the description does not disclose behavioral traits like side effects, permissions, or rate limits. It only states the basic function, leaving the agent uninformed about what happens during analysis.

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 (two sentences, ~21 words) and front-loaded with the key action. No filler, but could be slightly expanded for more 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?

Without an output schema, the description does not specify the return value format or structure. For a tool that 'suggests optimal search approaches,' this is a significant gap that hampers agent understanding of what to expect.

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 both parameters. The description adds context that the query_description is analyzed for patterns, but this does not significantly enhance understanding 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 indicates the tool analyzes search queries and suggests optimal approaches, distinguishing it from sibling direct-search tools. It specifies the resource ('search queries') and the action ('suggests optimal search approaches'). However, it could be more explicit about the output format.

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 given on when to use this tool versus the many sibling search tools. It implies use for strategic guidance, but lacks explicit conditions or alternatives.

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