Ensembl MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose with no ambiguity. For example, 'lookup_gene' retrieves detailed gene information, 'search_genes' finds genes by name or description, and 'get_transcripts' focuses on transcript structures, ensuring agents can easily differentiate between them.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as 'get_sequence', 'list_species', and 'search_genes'. This uniformity makes the toolset predictable and easy to navigate for agents.
Tool Count5/5
With 19 tools, the server is well-scoped for genomic data analysis, covering diverse operations like sequence fetching, variant analysis, and gene lookups. Each tool earns its place without feeling excessive or insufficient for the domain.
Completeness5/5
The toolset provides complete coverage for genomic workflows, including data retrieval (e.g., 'get_sequence'), analysis (e.g., 'get_variant_consequences'), and utilities (e.g., 'map_coordinates'). There are no obvious gaps, supporting comprehensive agent operations in this domain.
Average 2.9/5 across 19 of 19 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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. While 'look up' implies a read-only operation, it doesn't specify authentication requirements, rate limits, error handling, or what information is returned about each gene. The description lacks crucial behavioral context for a tool with 3 parameters and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a straightforward batch lookup tool and gets directly to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'look up' returns (gene details, sequences, annotations?), doesn't mention performance considerations for batch operations, and provides no context about the data source or limitations beyond what's in the parameter schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the schema already documents all parameters thoroughly (gene_ids with limits, species with default, format with enum). The description adds no additional parameter semantics beyond what's in the schema, so 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('look up') and target resource ('multiple genes simultaneously'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'lookup_gene' (singular) or 'search_genes', leaving some ambiguity about when to choose this batch version over alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'lookup_gene' or 'search_genes'. It mentions 'multiple genes simultaneously' which implies batch processing, but doesn't explicitly state this as the primary use case or provide any exclusion criteria or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden but offers minimal behavioral insight. It mentions fetching sequences but doesn't disclose critical traits like whether this is a read-only operation, potential rate limits, authentication requirements, or what happens with invalid inputs. The batch nature (max 50 items) is only hinted at in the schema, not the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 redundancy. It's front-loaded with the core action and scope, making it easy to parse. Every word contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a batch operation tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain return values, error handling, or performance considerations. The complexity of batch processing warrants more context, especially without structured fields to compensate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 parameters. The description adds no additional meaning beyond implying 'regions' can include 'features', which is already covered in the schema's description. No syntax examples or usage context are provided, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'fetch' and the resource 'sequences', specifying it's for 'multiple regions or features'. This distinguishes it from single-sequence tools like 'get_sequence' or 'get_cds_sequence' by emphasizing batch capability. However, it doesn't explicitly differentiate from all siblings like 'get_variants' which might also fetch sequences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 scenarios like bulk processing vs. single queries, or compare to siblings such as 'get_sequence' for individual regions or 'search_genes' for gene-based queries. The agent must infer usage from the name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 only states what the tool does ('Get genome assembly information and statistics') without mentioning important behavioral aspects like whether this is a read-only operation, what format the information comes in, potential rate limits, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a simple retrieval 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'information and statistics' includes, what format the results come in, or any behavioral constraints. Given the lack of structured metadata, the description should provide more complete context about what this tool actually returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter-specific information beyond what's already in the schema (which has 100% coverage). It doesn't explain what 'genome assembly information and statistics' includes or how parameters affect the output. With complete schema coverage, the baseline is 3 even without additional parameter context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('genome assembly information and statistics'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'get_karyotype' or 'list_species' that might also provide assembly-related information, preventing 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.
Usage Guidelines2/5
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 sibling tools like 'get_karyotype' and 'list_species' that might overlap in functionality, there's no indication of what distinguishes this tool or when it should be preferred over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 but offers minimal information. It mentions retrieving a phylogenetic tree but doesn't specify if this is a read-only operation, requires authentication, has rate limits, or what the output entails (e.g., tree structure, metadata). For a tool with 4 parameters and no output schema, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get phylogenetic tree for gene family') with zero wasted words. It avoids redundancy and is appropriately sized for the tool's complexity, making it easy to parse quickly while conveying the essential action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what a phylogenetic tree output looks like, how it's structured, or any behavioral aspects like error handling or data sources. While the schema covers inputs well, the lack of output information and behavioral context leaves significant gaps for an AI agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the input schema already documents all parameters thoroughly (e.g., 'gene_id' as Ensembl gene ID, 'format' with enum values). The description adds no additional semantic context beyond implying that parameters relate to fetching a tree for a gene family. Since the schema does the heavy lifting, a baseline score of 3 is appropriate, though the description doesn't compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('phylogenetic tree for gene family'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'get_homologs' or 'get_sequence' by focusing specifically on phylogenetic tree retrieval. However, it doesn't explicitly mention what a 'gene family' entails or how it relates to the input parameters, 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.
Usage Guidelines2/5
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. For example, it doesn't clarify if this should be used instead of 'get_homologs' for evolutionary analysis or how it differs from 'batch_gene_lookup' for gene information. Without any context on prerequisites, typical use cases, or comparisons to sibling tools, users must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 like rate limits, authentication needs, error handling, or output structure (e.g., what data is returned). For a tool with 5 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Find orthologous and paralogous genes across species.' It is front-loaded with the core purpose, has zero waste, and is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, no output schema, no annotations), the description is incomplete. It lacks details on behavioral traits, output format beyond the 'format' parameter, and usage context. Without annotations or output schema, the description should compensate more to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 meaning beyond the schema, such as explaining relationships between parameters (e.g., how 'species' and 'target_species' interact) 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.
Purpose4/5
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 orthologous and paralogous genes across species.' It specifies the verb ('find') and resource ('orthologous and paralogous genes'), making the action explicit. However, it doesn't distinguish this from sibling tools like 'get_gene_tree' or 'lookup_gene', which might involve related gene data, 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.
Usage Guidelines2/5
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 prerequisites, exclusions, or compare to siblings such as 'get_gene_tree' (which might involve phylogenetic trees) or 'lookup_gene' (which might retrieve basic gene info). Usage is implied by the purpose 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.
Behavior2/5
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 how it behaves—such as whether it's a read-only operation, what format the output takes, potential errors, or performance characteristics. This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with just one short phrase ('Get chromosome information and karyotype'), which is front-loaded and wastes no words. Every part of the description contributes directly to stating the tool's purpose, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 for a tool that likely returns complex genomic data. It doesn't explain what 'chromosome information and karyotype' entails, the format of the output, or any limitations, which could hinder an agent's ability to use the tool effectively in a broader context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 'species' fully documented in the schema. The description doesn't add any additional meaning or context about parameters beyond what the schema provides, so it meets the baseline score of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 a specific verb ('Get') and resource ('chromosome information and karyotype'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_assembly_info' or 'list_species' which might also provide related genomic information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 many sibling tools available (e.g., 'get_assembly_info', 'list_species'), there's no indication of specific use cases, prerequisites, or exclusions that would help an agent choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what the tool does but lacks critical details: it doesn't specify if this is a read-only operation, what the output format is (e.g., list of motifs, scores, or visualizations), or any limitations like rate limits or data availability. This is inadequate for a tool with potential complexity in genomic data retrieval.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of genomic data retrieval and the lack of annotations and output schema, the description is insufficient. It doesn't explain what 'motifs' entail (e.g., binding sites, scores, or sequences), how results are returned, or any behavioral traits like error handling. This leaves significant gaps for an agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the input schema already documents all three parameters with clear descriptions. The description adds no additional meaning beyond implying the tool operates on genomic regions, which is redundant with the schema. 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.
Purpose4/5
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 ('transcription factor binding motifs in genomic region'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'get_regulatory_features' or 'get_sequence', which might also retrieve genomic data, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 prerequisites, exclusions, or compare it to sibling tools like 'get_regulatory_features' that might overlap in functionality, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what the tool does but lacks critical behavioral details: it doesn't mention whether this is a read-only operation, what format the output takes, potential rate limits, authentication needs, or error conditions. For a tool with 4 parameters and no output schema, this leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that efficiently communicates the core functionality. It's front-loaded with the main purpose and includes helpful examples in parentheses. There's no wasted language or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no annotations, no output schema), the description is insufficiently complete. It doesn't explain what the tool returns, how results are structured, whether there are limitations on region size, or how optional parameters affect results. For a genomic query tool with multiple parameters, users need more context about output format and behavioral constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 minimal value beyond the schema - it mentions 'genomic region' which aligns with the 'region' parameter, and 'regulatory elements' which relates to 'feature_type', but provides no additional syntax, format, or usage details. 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.
Purpose4/5
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 ('regulatory elements') with specific examples (enhancers, promoters, TFBS) and scope ('in genomic region'). It distinguishes from siblings like get_motif_features or get_sequence by focusing on regulatory elements rather than motifs or raw sequences. However, it doesn't explicitly differentiate from all possible alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 get_motif_features (which might overlap for TFBS) or specify use cases like regulatory analysis versus gene lookup. There's no discussion of prerequisites, limitations, or comparative contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 critical behavioral details: it doesn't mention whether this is a read-only operation, potential rate limits, authentication needs, error handling, or what the output looks like (e.g., sequence format details). For a tool with 5 parameters and no output schema, 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.
Conciseness5/5
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 directly states what the tool does, making it easy to parse quickly. Every word earns its place, and there's no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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, and many sibling tools), the description is incomplete. It lacks behavioral context, usage differentiation, and output details. For a tool that retrieves biological data with multiple options, more guidance is needed to help an agent use it correctly without trial and error.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 minimal value beyond the schema: it implies 'region' accepts coordinates or IDs, but the schema already describes this as 'Genomic region (chr:start-end) or feature ID'. No additional syntax, examples, or constraints are provided. 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.
Purpose4/5
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 DNA sequence for genomic coordinates or gene/transcript ID'. It specifies the verb ('Get') and resource ('DNA sequence'), and indicates the input types (coordinates or IDs). However, it doesn't explicitly differentiate from siblings like 'get_cds_sequence' or 'translate_sequence', which also retrieve sequence-related data, leaving some ambiguity about when to choose this tool over those alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools. With many sequence-related siblings (e.g., get_cds_sequence, translate_sequence, batch_sequence_fetch), there's no indication of context, exclusions, or alternatives. The agent must infer usage from tool names alone, which is insufficient for reliable selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'detailed structure,' hinting at rich output, but doesn't specify what that includes (e.g., exon-intron boundaries, UTRs, coding sequences) or behavioral traits like rate limits, error handling, or data freshness. For a tool with no annotations, this leaves significant gaps in understanding how it operates beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Get all transcripts for a gene with detailed structure.' It is front-loaded with the core action and resource, with no wasted words. Every part earns its place by clarifying scope ('all transcripts') and output quality ('detailed structure'), making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (3 parameters, no annotations, no output schema), the description is incomplete. It lacks details on output format (e.g., JSON structure, fields included), error cases (e.g., invalid gene IDs), and behavioral context (e.g., performance, limitations). For a tool that retrieves biological data with potential nuances, more completeness is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all parameters well-documented in the input schema (e.g., 'gene_id' as Ensembl gene ID, 'species' with default, 'canonical_only' as boolean). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Baseline 3 is appropriate since 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.
Purpose4/5
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 all transcripts for a gene with detailed structure.' It specifies the verb ('Get'), resource ('transcripts'), and scope ('for a gene'), distinguishing it from siblings like 'get_sequence' or 'lookup_gene' that handle different data types. However, it doesn't explicitly differentiate from 'get_cds_sequence' or 'translate_sequence', which are also transcript-related but focus on specific aspects rather than comprehensive transcript details.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 prerequisites (e.g., needing a valid gene ID), exclusions (e.g., not for non-coding genes), or comparisons to siblings like 'batch_gene_lookup' for multiple genes or 'get_variant_consequences' for variant effects on transcripts. Usage is implied by the purpose but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'predict,' implying a computational or analytical operation, but doesn't detail aspects like whether this is a read-only query, potential rate limits, accuracy considerations, or output format. This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 unnecessary words. It's front-loaded and appropriately sized, making it easy to grasp quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of predicting variant consequences and the lack of annotations and output schema, the description is insufficient. It doesn't explain what the predictions entail, how results are returned, or any limitations, making it incomplete for effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters ('variants' and 'species'). The description adds no additional meaning beyond the schema, such as examples of variant IDs or species names, but since the schema is comprehensive, 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.
Purpose4/5
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 a specific verb ('predict') and resource ('consequences of variants on genes and transcripts'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_variants' or 'get_transcripts', which might handle related but different aspects of variant or transcript data, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools such as 'get_variants' and 'get_transcripts' available, there's no indication of scenarios where this tool is preferred, prerequisites, or exclusions, leaving usage unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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. While 'Get' implies a read-only operation, the description doesn't address critical behavioral aspects such as authentication requirements, rate limits, pagination, error handling, or what happens when no variants are found in the specified region. This leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a straightforward retrieval tool and front-loads the essential information, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of genomic data retrieval and the absence of both annotations and an output schema, the description is insufficiently complete. It doesn't explain what the tool returns (e.g., variant details, format specifics), how results are structured, or any limitations beyond the basic purpose, leaving too much undefined for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds no parameter semantics beyond what's already documented in the input schema, which has 100% coverage with clear descriptions for all four parameters. The baseline score of 3 reflects that the schema adequately documents parameters, but the description doesn't provide additional context about parameter interactions or usage examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 resource 'genetic variants in a genomic region', making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_variant_consequences' or 'get_sequence', which reduces clarity about its unique role in the toolset.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools like 'get_variant_consequences' and 'get_sequence' available, there's no indication of specific use cases, prerequisites, or exclusions that would help an agent choose appropriately among related genomic data retrieval tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 how it behaves—such as whether it's a read-only operation, what the output format looks like, potential rate limits, or error conditions. For a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently communicates the essential function without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 4 parameters, no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, output format, or usage context, leaving significant gaps for an AI agent to understand how to effectively invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description doesn't add any parameter-specific information beyond what's already in the input schema, which has 100% coverage. It doesn't explain the meaning or implications of parameters like 'all_levels' or 'external_db' in context. However, since the schema coverage is high, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and target resource ('external database cross-references for genes'), making the tool's purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'lookup_gene' or 'search_genes' which might also retrieve gene-related information, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 this tool is appropriate compared to siblings like 'lookup_gene' or 'search_genes', nor does it specify prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Get' operation (implying read-only), but doesn't mention any behavioral traits like rate limits, authentication requirements, pagination, response format, or what 'available' means in context. The description is too minimal for a tool with no 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.
Conciseness5/5
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 simple list operation and gets straight to the point without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what information is returned about species and assemblies, how results are structured, or any limitations. Given the complexity of biological data and the lack of structured documentation, more context is needed for an agent to use this effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage for its single parameter 'division', so the description doesn't need to add parameter details. The description doesn't mention the parameter at all, which is acceptable given the schema coverage. Baseline 3 is appropriate when the schema does the documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 resource 'list of available species and assemblies', making the purpose understandable. It doesn't explicitly differentiate from siblings like 'get_assembly_info' which might provide similar information, but the focus on 'available species' provides reasonable distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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_assembly_info' or 'batch_gene_lookup'. There's no mention of prerequisites, typical use cases, or limitations that would help an agent choose between this and sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 but only states the basic action ('Get detailed gene information'). It doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, error handling, or what 'detailed' entails beyond the parameters. This leaves significant gaps for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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. Every part ('Get detailed gene information by stable ID or symbol') contributes directly to understanding the tool, making it optimally concise and well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a gene lookup tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'detailed gene information' includes, how results are structured, or handle potential issues like invalid IDs. For a tool that likely returns rich biological data, more context is needed to guide an agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'stable ID or symbol' which aligns with the 'gene_id' parameter, but adds no further semantics beyond what the schema provides. With 100% schema description coverage, the baseline is 3, as the schema already documents all parameters thoroughly (e.g., 'expand' includes transcript/exon details, 'format' has enum values). The description doesn't compensate with additional context like examples or edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 ('detailed gene information') with specific identifiers ('stable ID or symbol'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'search_genes' or 'get_transcripts' which might also retrieve gene information, 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.
Usage Guidelines2/5
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_genes' for broader queries or 'batch_gene_lookup' for multiple genes. It lacks context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name and parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 search functionality but doesn't describe what the search returns (e.g., list of gene objects, metadata), pagination behavior, rate limits, authentication needs, or error conditions. For a search tool with 5 parameters, this leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 word contributing to understanding the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the search returns, how results are structured, or behavioral aspects like performance or limitations. The high schema coverage helps, but the overall context for agent usage is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter well-documented in the schema (e.g., query accepts partial matches, species defaults to homo_sapiens, feature has enum values, limit has range). The description adds no additional parameter semantics beyond what's already in the schema, so it meets the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'search' and resource 'genes', specifying what fields can be searched (name, description, or identifier). However, it doesn't explicitly differentiate from sibling tools like 'lookup_gene' or 'batch_gene_lookup', which might have different search approaches or scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 sibling tools for gene-related operations (e.g., 'lookup_gene', 'batch_gene_lookup', 'get_gene_tree'), there's no indication of this tool's specific use case, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what the tool does but doesn't describe important behavioral aspects: whether this is a read-only operation, what happens with invalid sequences, whether there are rate limits, what the output format looks like, or error conditions. For a bioinformatics tool with no annotation coverage, this represents 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that directly states the tool's function. Every word earns its place with no redundancy or unnecessary elaboration. It's front-loaded with the core purpose and doesn't waste space on obvious information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of sequence translation (which involves biological interpretation, genetic codes, and potential edge cases), the description is insufficient. With no annotations, no output schema, and sibling tools that might overlap in functionality, the description doesn't provide enough context for an agent to understand when and how to use this tool effectively. It states what happens but not the broader context of usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 both parameters thoroughly. The description mentions DNA sequence translation but doesn't add any parameter-specific information beyond what's in the schema (like explaining genetic code tables in biological terms or sequence format requirements). This meets the baseline for high schema coverage but doesn't provide additional semantic context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: translating DNA sequences to protein sequences. It specifies both the input (DNA sequence) and output (protein sequence), making the verb+resource relationship explicit. However, it doesn't differentiate from sibling tools like 'get_sequence' or 'get_cds_sequence' which might involve sequence retrieval rather than translation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 many sibling tools for sequence-related operations (like get_sequence, get_cds_sequence, get_transcripts), there's no indication of when translation is appropriate versus retrieving sequences or other operations. The description lacks any context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 clarify if this is a read-only operation, requires authentication, has rate limits, or what the output entails (e.g., format details beyond the schema). This leaves significant gaps in understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words, effectively front-loading the core purpose. It is appropriately sized for the tool's complexity, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 minimal but covers the basic purpose. It lacks details on output behavior, error handling, or integration with sibling tools, making it adequate but incomplete for full contextual understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema fully documents parameters like 'transcript_id', 'species', and 'format'. The description adds no additional semantic context beyond what the schema provides, such as examples or edge cases, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 resource 'coding sequence (CDS) for a transcript', making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_sequence' or 'translate_sequence', which might handle similar biological data, leaving some ambiguity in tool selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'get_sequence' or 'translate_sequence'. It lacks context about prerequisites, exclusions, or specific scenarios where this tool is preferred, offering minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 tool's function but lacks critical behavioral details: it doesn't specify if this is a read-only operation (likely, but not confirmed), what the output format is (since no output schema exists), potential rate limits, error conditions (e.g., invalid assemblies), or whether it's a batch or single conversion. For a tool with 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.
Conciseness5/5
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 or redundant information. It's front-loaded with the core action ('Convert coordinates'), making it immediately clear. Every word earns its place, and there's no waste or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (coordinate conversion between genome assemblies is a non-trivial genomic operation), lack of annotations, and absence of an output schema, the description is insufficiently complete. It doesn't explain what the tool returns (e.g., mapped coordinates, errors), behavioral traits like idempotency or side effects, or usage context. For a tool with no structured output or annotations, the description should provide more context to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 documented in the schema itself (e.g., 'region' as 'Genomic region (chr:start-end)'). The description adds no additional parameter semantics beyond the schema, such as examples, format constraints, or default behaviors for optional parameters like 'species'. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't enhance parameter understanding but doesn't need to compensate for gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Convert coordinates') and the resource involved ('between genome assemblies'). It precisely distinguishes this tool from all sibling tools, which perform different genomic operations like gene lookup, sequence fetching, or variant analysis, none of which involve coordinate conversion between assemblies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. While it's clear from the purpose that this is for coordinate conversion, there's no mention of prerequisites (e.g., needing a source assembly), exclusions, or related tools like 'get_assembly_info' that might provide assembly details. The agent must infer usage solely from the tool name and parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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