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 mentions 'autocomplete functionality' and 'partial names,' implying a fuzzy search, but doesn't describe key behaviors like response format, error handling, rate limits, or authentication needs. For a search tool with zero annotation coverage, this is a significant gap in 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 a single, efficient sentence that front-loads the core purpose without unnecessary details. It avoids redundancy and wastes no words, making it highly concise and well-structured for quick understanding.

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 complexity of a search tool with no annotations and no output schema, the description is incomplete. It lacks details on what the tool returns (e.g., list of organisms with IDs), how results are ordered, or any limitations. This makes it inadequate for an AI agent to fully understand the tool's behavior and output.

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 description coverage is 100%, with clear descriptions for both parameters (partialName and rows). The description adds minimal value beyond the schema, as it only reiterates 'partial names' without providing additional context like examples beyond those in the schema or usage nuances. Baseline 3 is appropriate since the schema does the heavy lifting.

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 organisms with autocomplete functionality using partial names.' It specifies the verb ('Search'), resource ('organisms'), and key functionality ('autocomplete'), distinguishing it from sibling tools like search_by_scientific_name or search_by_vernacular_name. However, it doesn't explicitly differentiate from all siblings, such as explore_taxonomy, which might also involve searching.

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. It mentions 'autocomplete functionality' but doesn't specify scenarios (e.g., for quick suggestions during user input) or exclusions (e.g., not for exact matches). With multiple search-related siblings like search_by_scientific_name, the lack of comparative context leaves usage ambiguous.

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. It mentions 'finding related organisms' but lacks details on permissions, rate limits, data sources, or response format (e.g., list of species with attributes). For a tool with 3 parameters and no output schema, this leaves significant gaps in understanding how it behaves and what to expect.

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 that front-loads the core purpose ('Explore taxonomic relationships') and adds key context ('by finding related organisms at different taxonomic levels'). There is zero waste, and every word contributes to understanding the tool's function, making it appropriately sized and well-structured.

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 (3 parameters, no annotations, no output schema), the description is incomplete. It lacks behavioral details (e.g., what 'related organisms' means in practice), usage guidelines, and output expectations. While concise, it doesn't provide enough context for an agent to fully understand how to invoke and interpret results, especially without structured support from annotations or 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 schema fully documents all parameters. The description adds no additional meaning beyond the schema's details (e.g., it doesn't explain how 'level' affects results or provide examples beyond the enum). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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: 'Explore taxonomic relationships by finding related organisms at different taxonomic levels.' It specifies the verb ('explore') and resource ('taxonomic relationships'), and distinguishes it from siblings like 'get_hierarchy' or 'search_by_scientific_name' by focusing on related organisms rather than hierarchical or search functions. However, it doesn't explicitly contrast with all siblings (e.g., 'search_by_rank'), keeping it from a perfect score.

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. It mentions 'different taxonomic levels' but doesn't specify contexts or exclusions, such as when to prefer 'get_hierarchy' for full lineage or 'search_by_rank' for broader queries. Without explicit when/when-not instructions or named alternatives, it offers minimal 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 carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe behavioral traits such as whether it's read-only, potential rate limits, error handling, or the format of the returned hierarchy. For a tool with no annotations, this leaves significant gaps in understanding its operation.

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 that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with every part contributing to clarity. There's no waste or 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 complexity of a taxonomic hierarchy tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., structure, fields), potential limitations, or how it integrates with sibling tools. For a tool that likely returns structured data, more context is needed to be fully helpful.

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 minimal meaning beyond the input schema, which has 100% coverage and clearly defines the 'tsn' parameter. It implies the parameter is required but doesn't provide additional context like TSN format examples or constraints. With high schema coverage, the baseline is 3, and the description doesn't 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 the action ('Get') and the resource ('complete taxonomic hierarchy') with a specific input requirement ('for a given TSN'). It distinguishes from siblings like 'search_by_tsn' by focusing on hierarchy retrieval rather than search, though it doesn't explicitly mention this distinction. The purpose is specific but could be slightly more differentiated.

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. It doesn't mention when to choose it over siblings like 'search_by_tsn' or 'explore_taxonomy', nor does it specify prerequisites or exclusions. Usage is implied by the name and description alone, with no explicit 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 provided, the description carries full burden for behavioral disclosure. It mentions 'random species' and 'optional taxonomic filters' but doesn't describe what 'random' means (uniform distribution? seeded?), whether results are reproducible, rate limits, authentication requirements, or what format the species data returns. For a tool with 9 parameters and no annotation coverage, this 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 a single, efficient sentence that front-loads the core functionality ('Get random species') followed by key constraint ('from ITIS database') and important feature ('with optional taxonomic filters'). Every word earns its place with zero waste.

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 9 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'random' means operationally, what data fields are returned, whether results are paginated, or any behavioral constraints. The single sentence leaves too many questions unanswered for proper agent usage.

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

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

Schema description coverage is 100%, so the schema already documents all 9 parameters thoroughly. The description adds minimal value beyond what's in the schema - it mentions 'optional taxonomic filters' which aligns with the schema's taxonomic parameters, but doesn't provide additional semantic context. Baseline 3 is appropriate when schema does the heavy lifting.

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' and resource 'random species from ITIS database', making the purpose evident. It distinguishes itself from siblings by focusing on random selection rather than search or exploration functions. However, it doesn't explicitly contrast with all siblings like 'get_statistics' which might also retrieve species 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 mentions 'optional taxonomic filters' which implies some context for usage, but provides no explicit guidance on when to use this tool versus alternatives like 'search_by_scientific_name' or 'search_by_vernacular_name'. There's no mention of when random sampling is preferable to targeted 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get'), implying it's non-destructive, but doesn't mention any behavioral traits like rate limits, authentication needs, response format, or whether it's real-time vs cached data. This is a significant gap for a tool with zero annotation coverage.

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 that directly states the tool's purpose without any fluff. It's front-loaded with the core action and resource, making it easy to parse. 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 the tool has 0 parameters, no annotations, and no output schema, the description is minimally adequate. It explains what the tool does but lacks details on behavioral context, output format, or usage scenarios. For a simple read tool, this might suffice, but it leaves gaps in understanding how to interpret results.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, and the baseline for this scenario is 4, as it avoids unnecessary details while being complete for a parameterless tool.

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') and resource ('basic statistics about the ITIS database'), specifying it returns 'total number of records'. However, it doesn't explicitly differentiate this from sibling tools like 'search_itis' or 'explore_taxonomy', which might also provide statistical insights.

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 mentions 'basic statistics' but doesn't clarify if this is for summary overviews, how it differs from search tools, or any prerequisites. This leaves the agent without context for tool selection.

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 mentions 'search' but doesn't describe what the search returns (e.g., list of organisms, taxonomic details), whether it's paginated (though the schema hints at this), error handling, or rate limits. For a search tool with zero annotation coverage, this leaves significant behavioral gaps.

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 that states the tool's purpose clearly without unnecessary words. It's appropriately sized and front-loaded, with every part of the sentence contributing essential information.

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

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

Given the tool's moderate complexity (search with pagination), no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, output format, and usage guidelines. With schema coverage at 100%, the input parameters are well-documented, but the overall context remains incomplete for effective 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 100%, so the schema already documents all three parameters (kingdom, rows, start) with descriptions and defaults. The description adds no additional parameter semantics beyond what's in the schema. According to the rules, with high schema coverage (>80%), the baseline is 3 even with no param info in 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's purpose: 'Search for organisms within a specific kingdom in ITIS database.' It specifies the verb ('search'), resource ('organisms'), and scope ('within a specific kingdom in ITIS database'). However, it doesn't explicitly distinguish this tool from sibling tools like 'search_by_rank' or 'search_itis', which likely have overlapping functionality.

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. It doesn't mention sibling tools like 'search_by_rank' or 'search_itis', nor does it specify prerequisites or exclusions. The context is implied (searching by kingdom), but no explicit usage guidelines are 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions searching in the 'ITIS database', which implies a read-only operation, but doesn't detail aspects like rate limits, authentication needs, error handling, or what the search results entail (e.g., format, fields). For a search tool with zero annotation coverage, this leaves significant gaps in understanding its 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 a single, efficient sentence: 'Search for organisms by their taxonomic rank in ITIS database.' It is front-loaded with the core purpose, has no unnecessary words, and earns its place by clearly stating the tool's function. This is an excellent example of conciseness.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks details on behavioral traits, usage context, and result handling. Without an output schema, it doesn't explain return values, which could be a gap. However, it covers the basic purpose, making it just sufficient for a simple search operation.

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

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

The input schema has 100% description coverage, with clear explanations for 'rank', 'rows', and 'start'. The description adds no additional parameter semantics beyond what the schema provides, such as examples of valid ranks or pagination behavior. Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 organisms by their taxonomic rank in ITIS database.' It specifies the verb ('Search'), resource ('organisms'), and constraint ('by their taxonomic rank'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'search_by_kingdom' or 'search_by_scientific_name', which also search the ITIS database but by different criteria, so it falls short of a perfect score.

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. It doesn't mention sibling tools such as 'search_by_kingdom' or 'search_by_scientific_name', nor does it specify scenarios where taxonomic rank-based search is preferred over other search methods. Without this context, users might struggle to choose the right tool for their 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It only states what the tool does at a high level, without mentioning rate limits, authentication needs, error conditions, pagination behavior beyond the parameters, or what the search returns (e.g., partial matches, exact matches). This is inadequate for a search tool with multiple parameters.

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 with zero wasted words. It's appropriately sized for a straightforward search tool and front-loads the core purpose immediately.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the search returns (e.g., taxonomic details, match types), error handling, or limitations. For a search tool with three parameters and multiple sibling alternatives, this leaves significant gaps in understanding how to use it effectively.

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 description coverage is 100%, with all parameters well-documented in the schema itself. The description doesn't add any meaningful parameter semantics beyond what's already in the schema (e.g., it doesn't clarify search behavior like case sensitivity or wildcard support). Baseline 3 is appropriate when the schema does the heavy lifting.

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 for') and resource ('organisms by their scientific name in ITIS database'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'search_by_vernacular_name' or 'search_itis', which appear to be related search functions in the same database.

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 'search_by_vernacular_name', 'search_by_kingdom', or 'search_itis'. It doesn't mention prerequisites, limitations, or comparative use cases, leaving the agent to guess based on tool names alone.

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. It states this is a search operation but doesn't describe what kind of results to expect, whether it's paginated, if there are rate limits, authentication requirements, or error conditions. For a search tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

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 that communicates the essential purpose without any wasted words. It's appropriately sized for a single-parameter search tool and gets straight 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 search tool with no annotations and no output schema, the description is insufficiently complete. It doesn't describe what the search returns (organism details? taxonomy hierarchy? just existence?), nor does it address common search considerations like partial matches, case sensitivity, or error handling for invalid TSNs.

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 description coverage is 100%, with the single parameter 'tsn' fully documented in the schema. The description doesn't add any additional parameter semantics beyond what the schema already provides (that it searches by TSN), so it meets the baseline of 3 for high schema coverage.

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 for organisms') and the resource ('by their Taxonomic Serial Number (TSN) in ITIS database'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its many siblings (like 'search_by_scientific_name' or 'search_itis'), which would require a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. With multiple search-related sibling tools available, there's no indication of when TSN-based searching is appropriate versus other search methods like by name, kingdom, or rank.

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 mentions searching in the ITIS database but doesn't disclose behavioral traits like whether it's read-only, potential rate limits, authentication needs, or what the output looks like (e.g., format, pagination details). For a search tool with zero annotation coverage, this is a significant gap.

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 that front-loads the core purpose without unnecessary words. It's appropriately sized for a simple search tool, with zero waste or redundancy.

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

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

Given the tool's moderate complexity (search with pagination), lack of annotations, and no output schema, the description is incomplete. It doesn't explain return values, error handling, or behavioral context, leaving gaps for an AI agent to understand how to use it effectively beyond basic input.

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 documents all three parameters (vernacularName, rows, start) with clear descriptions. The description adds no additional parameter semantics beyond what's in the schema, such as examples or constraints. Baseline 3 is appropriate when the schema does the heavy lifting.

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 organisms by their common/vernacular names in ITIS database.' It specifies the verb ('Search'), resource ('organisms'), and scope ('ITIS database'), distinguishing it from siblings like search_by_scientific_name. However, it doesn't explicitly differentiate from search_itis or autocomplete_search, which might also involve searching.

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. It doesn't mention when to prefer this over search_by_scientific_name or other search siblings, nor does it specify prerequisites or exclusions. Usage is implied by the name but not explicitly 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'flexible query parameters' and 'general search,' but fails to describe critical behaviors: it doesn't specify if this is a read-only operation, what the output format looks like (especially without an output schema), potential rate limits, authentication needs, or error handling. For a search tool with 6 parameters and no annotations, this is a significant gap in 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 concise with two sentences that efficiently state the tool's function and key feature ('flexible query parameters'). There's no unnecessary repetition or fluff, and it's front-loaded with the core purpose. However, it could be slightly more structured by explicitly mentioning it's a general-purpose search compared to siblings.

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 complexity (6 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It doesn't explain the return format, error conditions, or how results are structured, which is critical for a search tool. Without annotations or output schema, the agent lacks guidance on what to expect, making it inadequate for informed tool selection and invocation.

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

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

The description adds minimal value beyond the input schema, which has 100% coverage with detailed parameter descriptions. It vaguely references 'flexible query parameters' but doesn't explain how parameters interact (e.g., that 'filters' might override parts of 'query') or provide usage examples beyond what's in the schema. Since schema coverage is high, the baseline is 3, and the description doesn't 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 the tool's purpose: 'Search ITIS database using SOLR queries.' It specifies the verb ('Search'), resource ('ITIS database'), and method ('SOLR queries'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'search_by_scientific_name' or 'search_by_kingdom', which are more specific search methods.

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 minimal usage guidance with 'Supports general search with flexible query parameters,' implying this is a broad, flexible tool. However, it doesn't specify when to use this tool versus more targeted sibling tools (e.g., 'search_by_scientific_name' for exact matches or 'search_by_kingdom' for kingdom-based searches), nor does it mention exclusions or prerequisites. This lack of explicit comparison leaves the agent guessing about the best tool choice.

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