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 endpoint categories but doesn't describe what the tool actually returns (e.g., tree structures, alignment formats, homology lists), performance characteristics, rate limits, authentication needs, or error conditions. For a complex tool with 8 parameters and multiple analysis types, this is insufficient 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 efficiently structured in two sentences: first stating the broad purpose, then listing endpoint categories. It's appropriately sized for the tool's complexity. However, the endpoint listing could be more clearly integrated with the purpose statement rather than appearing as an afterthought.

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 complex comparative genomics tool with 8 parameters, multiple analysis types, no annotations, and no output schema, the description is incomplete. It doesn't explain what results to expect for different analysis types, how gene trees vs homology vs alignments differ in output, or provide any examples of typical use cases. The agent would struggle to understand what this tool actually returns.

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 8 parameters thoroughly with descriptions, enums, defaults, and constraints. The description adds minimal value beyond the schema - it mentions endpoint categories that loosely map to analysis_type values but doesn't provide additional parameter context, validation rules, or usage examples. 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 tool's purpose as 'Comparative genomics: gene trees, homology, species alignments, and evolutionary analysis' and mentions specific endpoint categories. It distinguishes from siblings by focusing on comparative genomics rather than feature overlap, lookup, mapping, etc. However, it doesn't explicitly contrast with each sibling 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?

The description provides no guidance on when to use this tool versus the sibling tools. While it mentions endpoint categories, it doesn't explain scenarios where comparative genomics analysis is preferred over feature overlap, sequence retrieval, variation analysis, or other sibling capabilities. No alternatives or exclusions 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context: 'Automatically handles assembly-specific format variations' and 'Covers /overlap/region and /overlap/id endpoints,' which helps the agent understand implementation details. However, it doesn't cover critical behavioral aspects like rate limits, error handling, response format, or whether this is a read-only operation (though 'Find' implies it likely is).

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 appropriately sized (three sentences) and front-loaded with the core purpose. Every sentence adds value: the first states the purpose, the second adds behavioral context (format handling), and the third specifies endpoints. There's no wasted text, though it could be slightly more structured for clarity.

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

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

Given the tool's moderate complexity (5 parameters, no output schema, no annotations), the description is partially complete. It covers the purpose and some behavioral context but lacks details on output format, error cases, or performance characteristics. Without annotations or output schema, the agent might struggle to interpret results fully, making this description adequate but with clear 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%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific semantics beyond what's in the schema (e.g., it doesn't explain format variations for 'region' beyond the schema's examples). Baseline 3 is appropriate when the schema does the heavy lifting, though the description could have enhanced understanding of parameter interactions.

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: 'Find genomic features (genes, transcripts, regulatory elements) that overlap with a genomic region or specific feature.' It specifies the verb ('Find') and resource ('genomic features'), and mentions the types of features covered. However, it doesn't explicitly differentiate this tool from its siblings (e.g., ensembl_lookup, ensembl_mapping), which would be needed for a score of 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 implies usage context by mentioning 'genomic region or specific feature' and the endpoints covered, but it doesn't provide explicit guidance on when to use this tool versus alternatives like ensembl_lookup or ensembl_mapping. The input schema's 'oneOf' constraint (region OR feature_id) offers some usage rules, but the description itself lacks clear when/when-not instructions or named alternatives.

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 the tool 'covers' specific endpoints but doesn't describe response formats, error conditions, rate limits, authentication needs, or whether it's read-only versus mutative. For a tool with 5 parameters and no 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 appropriately sized with two sentences that efficiently convey scope and endpoint coverage. It's front-loaded with the core purpose and avoids unnecessary elaboration, though the second sentence could be slightly more polished.

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

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

For a tool with 5 parameters, no annotations, and no output schema, the description provides adequate purpose and scope but lacks behavioral context and output expectations. It's complete enough to understand what the tool does but insufficient for an agent to fully predict how to use it effectively without trial and error.

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 5 parameters thoroughly with examples and defaults. The description adds minimal value beyond the schema by mentioning endpoint coverage, but doesn't provide additional parameter semantics, syntax details, or usage patterns beyond what's in the structured fields.

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 with specific verbs ('look up', 'get cross-references', 'perform ID translation') and resources ('genes, transcripts, variants'), distinguishing it from siblings by mentioning specific endpoints (/lookup/*, /xrefs/*, variant_recoder) that other tools likely don't cover.

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 through endpoint references but doesn't explicitly state when to use this tool versus alternatives like ensembl_mapping or ensembl_variation. It provides context about what the tool covers but lacks explicit guidance on tool selection among 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but lacks details on behavioral traits such as rate limits, authentication needs, error handling, or what the output looks like (e.g., format, structure). For a tool with 6 parameters and no output schema, 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 and front-loaded, stating the core purpose in a single sentence. It avoids unnecessary details and wastes no words. However, it could be slightly more structured by explicitly separating coordinate system mapping from assembly mapping for clarity.

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

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

Given the complexity (6 parameters, no annotations, no output schema), the description is incomplete. It doesn't address output format, error cases, or usage context relative to siblings. For a mapping tool with multiple parameter dependencies, more guidance on behavior and results 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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain interactions between parameters like how feature_id relates to mapping_type). Baseline 3 is appropriate when the schema does the heavy lifting, but the description doesn't compensate with extra insights.

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: mapping coordinates between different coordinate systems and genome assemblies. It specifies the scope with 'genomic ↔ cDNA/CDS/protein' and mentions coverage of '/map/* endpoints.' However, it doesn't explicitly differentiate this tool from its siblings (e.g., ensembl_sequence or ensembl_variation), which might also involve coordinate handling.

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 coverage of '/map/* endpoints' but doesn't explain when mapping is needed compared to other Ensembl tools like ensembl_lookup or ensembl_sequence. There are no explicit when/when-not statements or references to sibling tools for 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 the full burden of behavioral disclosure. It describes what information can be retrieved (metadata, releases, species info, status) and the endpoints covered, but doesn't mention rate limits, authentication requirements, response formats, or error conditions. The description is informative but lacks operational details.

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 perfectly concise with two sentences that each earn their place. The first sentence states the purpose comprehensively, and the second sentence provides important implementation context about the endpoints covered. No wasted words.

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 4-parameter tool with no annotations and no output schema, the description provides good purpose and endpoint context but lacks information about return values, error handling, and operational constraints. Given the complexity of the tool (multiple parameter combinations), more behavioral context would be 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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain parameter interactions or provide examples). 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 with specific verbs ('Get server metadata, data releases, species info, and system status') and resources ('/info/* endpoints and /archive/id'), distinguishing it from sibling tools focused on compara, features, lookup, mapping, etc. It explicitly covers what information can be retrieved.

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 by mentioning the specific API endpoints covered ('/info/* endpoints and /archive/id'), which helps understand when to use this tool. However, it doesn't explicitly state when NOT to use it or name alternatives among siblings, though the distinction is implied by the different tool names.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'search' and 'traversal' operations but doesn't specify whether these are read-only, have rate limits, require authentication, or what format results return. For a tool with 5 parameters and complex logic (multiple required parameter combinations via anyOf), 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 extremely concise (one sentence) and front-loaded with the core functionality. Every word earns its place by specifying the domain (ontology/taxonomy), operations (search/traversal), and examples of what can be searched. There's zero redundancy or wasted verbiage.

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

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

For a tool with 5 parameters, complex conditional requirements (anyOf with three alternative required sets), no annotations, and no output schema, the description is insufficient. It doesn't explain how the different parameter combinations work together, what the tool returns, or the scope of operations. The agent must rely entirely on the input schema to understand functionality.

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 parameters thoroughly with descriptions and enums. The description adds minimal value beyond the schema by mentioning the types of ontologies and taxonomy, but doesn't provide additional context about parameter interactions or usage patterns. The baseline of 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: 'Ontology term search and NCBI taxonomy traversal' with specific examples of what can be searched (GO terms, phenotype ontologies, taxonomic classifications). It distinguishes itself from sibling tools by focusing on ontology/taxonomy operations rather than sequence, variation, or comparative genomics tools. However, it doesn't explicitly differentiate from potential overlapping functionality in sibling tools.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, constraints, or scenarios where this tool is preferred over other search or traversal methods. The agent must infer usage from the description alone without explicit 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 the action 'Get' but does not describe any behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like (e.g., structured data or raw text). This leaves significant gaps for an agent to understand how to interact with the tool effectively.

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 key information ('Get protein-level features, domains, and annotations') without any unnecessary words or redundancy. It is appropriately sized for the tool's purpose and structure, making it easy to parse quickly.

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 tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It does not address behavioral aspects, output expectations, or usage context, which are critical for an agent to use the tool correctly. The high schema coverage helps with parameters, but overall, the description lacks sufficient detail for full contextual understanding.

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

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

The schema description coverage is 100%, meaning all parameters are well-documented in the input schema itself. The description does not add any additional meaning beyond what the schema provides, such as explaining relationships between parameters or usage examples. With high schema coverage, the baseline score is 3, as the description does not compensate but also does not 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 verb 'Get' and the resources 'protein-level features, domains, and annotations for proteins and translations', making the purpose specific and understandable. However, it does not explicitly distinguish this tool from sibling tools like ensembl_feature_overlap or ensembl_sequence, which might also retrieve features or sequences, so it lacks sibling differentiation.

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, such as which sibling tools might be better for different types of data (e.g., ensembl_variation for variants or ensembl_sequence for sequences). There is no mention of prerequisites, exclusions, or specific contexts for usage, leaving the agent without clear 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 'Get' which implies a read-only operation, but doesn't specify if this requires authentication, has rate limits, returns paginated results, or details error conditions. The mention of 'regulatory overlap endpoints' hints at API behavior but lacks specifics like response format or performance characteristics, leaving significant gaps for a tool with 5 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 concise and front-loaded, stating the core purpose in the first clause. Both sentences earn their place: the first defines what the tool gets, and the second clarifies the scope of coverage. There's no redundant or vague language, making it efficient 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 (5 parameters, no annotations, no output schema), the description is incomplete. It lacks behavioral details (e.g., read/write nature, error handling), usage guidelines compared to siblings, and explanation of return values. While the schema covers parameters well, the description doesn't compensate for missing annotations or output schema, making it inadequate for full agent understanding.

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

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

The input schema has 100% description coverage, providing clear documentation for all 5 parameters (region, protein_id, binding_matrix_id, species, feature_type). The description adds no additional parameter semantics beyond what's in the schema—it doesn't explain relationships between parameters (e.g., that region, protein_id, and binding_matrix_id are alternative inputs) or provide usage examples. 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: 'Get regulatory features, binding matrices, and regulatory annotations.' It specifies the types of data retrieved (regulatory features, binding matrices, annotations) and mentions coverage of regulatory overlap endpoints and binding matrix data. However, it doesn't explicitly differentiate this tool from its siblings like 'ensembl_feature_overlap' or 'ensembl_protein_features', which likely handle related genomic 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 provides no guidance on when to use this tool versus alternatives. It mentions 'Covers regulatory overlap endpoints and binding matrix data' but doesn't clarify if this is exclusive to this tool or shared with siblings. There's no mention of prerequisites, typical use cases, or comparisons to other tools in the Ensembl suite, leaving the agent without context for 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 the endpoints covered but fails to describe key behavioral traits: it doesn't specify if this is a read-only operation, potential rate limits, authentication needs, error handling, or what the output looks like (e.g., sequence data structure). For a tool with 5 parameters and no annotations, this leaves significant gaps in understanding how it behaves.

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, stating the core purpose in the first sentence. The second sentence adds endpoint context without redundancy. Both sentences earn their place by clarifying scope, though it could be slightly more structured (e.g., bullet points for endpoints). No wasted words are present.

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 (5 parameters, no annotations, no output schema), the description is incomplete. It lacks behavioral details (e.g., read-only status, error cases), output format explanations (beyond the 'format' parameter), and guidance on sibling tool differentiation. For a sequence retrieval tool with multiple parameters and no structured output schema, more context is needed to ensure the agent can 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?

Schema description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds minimal value beyond the schema: it implies the tool handles both ID-based and region-based queries via the endpoints mentioned, but doesn't elaborate on parameter interactions or provide examples beyond what's in the schema. With high schema coverage, the 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 tool's purpose: 'Retrieve DNA, RNA, or protein sequences for genes, transcripts, regions.' It specifies the verb ('retrieve') and resources (sequences for various biological entities), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like ensembl_lookup or ensembl_feature_overlap, which might also retrieve sequence-related 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 provides minimal usage guidance: it mentions covering '/sequence/id and /sequence/region endpoints,' which hints at two use cases (ID-based vs. region-based retrieval). However, it lacks explicit guidance on when to use this tool versus alternatives (e.g., ensembl_lookup for general feature info or ensembl_protein_features for protein-specific data). No exclusions or prerequisites are 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 analysis types and endpoints but fails to describe critical traits: whether operations are read-only or mutative, authentication needs, rate limits, error handling, or output format. For a tool with 8 parameters and complex genomic analysis, this lack of behavioral context 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 appropriately concise and front-loaded, stating the core purpose in the first phrase. It uses a semicolon-separated list for analysis types and a brief endpoint summary, with no redundant sentences. However, the endpoint list ('Covers /variation/*, /vep/*, /ld/*, /phenotype/* endpoints.') could be integrated more smoothly, slightly affecting flow.

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 (8 parameters, no output schema, no annotations), the description is incomplete. It lacks output details, behavioral traits, and usage guidelines, which are crucial for an AI agent to invoke it correctly in genomic contexts. The high schema coverage helps with parameters, but overall, the description doesn't compensate for missing structured data.

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%, so the schema already documents all 8 parameters thoroughly. The description adds minimal value beyond the schema by listing analysis types (e.g., 'VEP consequence prediction') that map to the 'analysis_type' enum, but it doesn't provide additional syntax, format details, or interdependencies. This meets the baseline 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 tool's purpose: 'Variant analysis: VEP consequence prediction, variant lookup, LD analysis, phenotype mapping, haplotypes.' It provides specific verbs (prediction, lookup, analysis, mapping) and resources (variants, phenotypes, haplotypes), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'ensembl_lookup' or 'ensembl_feature_overlap,' which might offer overlapping genomic analysis capabilities.

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 lists analysis types and endpoints but doesn't specify prerequisites, exclusions, or comparisons to sibling tools. For example, it doesn't clarify if this is the primary tool for variant data or when to choose it over 'ensembl_lookup' for similar queries, leaving the agent without usage context.

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