hgnc-link

Server Quality Checklist

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Latest release: v2.1.2
Disambiguation5/5
All nine tools have clearly distinct purposes: gene retrieval, cross-references, group browsing, diagnostics, capabilities, reverse lookup, single/batch symbol resolution, and free-text search. There is no overlap or ambiguity between any two tools.
Naming Consistency5/5
Tool names follow a consistent verb_noun pattern (e.g., get_gene, resolve_symbol, search_genes). The verbs are either get, resolve, or search, each clearly indicating the action, and the nouns specify the target. No mixing of conventions.
Tool Count5/5
With 9 tools, the server is well-scoped for the HGNC nomenclature domain. Each tool serves a distinct and necessary function (lookup, batch, search, cross-references, etc.), and the count is neither too sparse nor overwhelming.
Completeness5/5
The tool surface covers all core operations for a gene nomenclature service: single and batch resolution, forward and reverse cross-reference mapping, group browsing, free-text search, and server diagnostics/capabilities. There are no obvious missing operations for the stated purpose.
Average 4.5/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 73 commits in the last 12 weeks
- Last stable release on August 10, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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}
```
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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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, open-world. The description adds valuable behavioral details: unknown database keys yield invalid_input+did-you-mean, databases overrides response_mode, and the signature. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose and parameter highlights, but includes a signature line. Nearly all sentences add value; minor redundancy with schema examples. Overall efficient.
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?
No output schema is provided, but the description does not explain the return format (e.g., list of objects with fields). For a complex tool with three parameters, this gap reduces completeness. However, the description covers input and behavior well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameters have 100% schema coverage. The description adds meaning beyond schema by listing database options, explaining response_mode tiers (minimal, compact, standard, full), and the override behavior with databases.
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 explicitly states the tool returns external database cross-references for a gene, listing many databases and explaining response_mode and databases parameters. It differentiates from sibling tools like get_gene (gene details) and resolve_gene_by_xref (reverse mapping).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions resolving the gene first and how parameters work, but does not explicitly compare to alternatives like resolve_gene_by_xref for reverse mapping. Usage context is clear but lack of when-not-to-use slightly lowers score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and not destructive. The description adds behavioral context about version suffix handling and transcript resolution, which goes beyond annotations without contradiction.
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?
Two concise sentences plus a signature line. Every sentence is purposeful, no redundancy. The core purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does not explain return format, but for a lookup tool with annotations, the input guidance is sufficient. Missing mention of multiple/no results is minor.
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 baseline is 3. The description adds examples and explains source synonyms and version suffix handling, providing minor added value over the schema.
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 it is a 'reverse identifier mapping' to 'find the HGNC gene(s) for an external database id', specifying verb and resource. It distinguishes from siblings like resolve_symbol (resolves symbols) and get_gene_cross_references (retrieves existing xrefs).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context with examples of source and value, tolerates version suffixes and MANE Select transcripts. It implicitly differentiates from alternatives but lacks explicit when-not-to-use statements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnly, openWorld, idempotent, and non-destructive hints. The description adds case-insensitivity, return format {hgnc_id, approved_symbol, match_type}, and error behavior (ambiguous returns candidates, not_found redirects). No contradictions.
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?
Three concise sentences: purpose, input/output/error details, and signature. No wasted words; each sentence serves a distinct purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers inputs, outputs, and error cases. With 2 parameters and 100% schema coverage, the description sufficiently explains behavior. Lacks definition of response_mode verbosity levels, but output schema is absent; still adequate for most agents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning beyond schema: explains query parameter accepts symbols/aliases/HGNC ids, and lists response_mode enum values with default 'compact'. However, it does not detail what each verbosity level returns; output schema is absent but description compensates with return fields.
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 tool resolves any gene symbol or HGNC id to canonical record, specifying input types (current, previous, alias, HGNC id) and output fields. It distinguishes from siblings like resolve_gene_by_xref and resolve_symbols_batch by focusing on symbol/HGNC resolution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly lists accepted inputs and mentions error handling (ambiguous_query with candidate list, not_found redirect). However, it does not explicitly state when to use alternatives like search_genes or get_gene, but the sibling list provides context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, open-world, idempotent, non-destructive. Description adds specifics: lists returned fields, explains response_mode effect (compact drops dates/provenance, minimal keeps identity+anchor ids). No contradictions.
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?
Two sentences: first describes purpose and data, second gives signature. No unnecessary words, front-loaded with key info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 2 params fully described in schema and annotations, description covers return contents and response_mode variations. No output schema needed because description lists fields explicitly. Completeness excellent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions and examples. Description goes beyond schema by explaining that response_mode controls verbosity with concrete examples (compact drops dates/provenance, minimal keeps identity+anchor ids).
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?
Description clearly states it returns the full HGNC record for a gene, specifies input types (HGNC id, symbol, alias), and lists contents (name, status, location, cross-refs). Distinguishes from siblings like resolve_symbol and search_genes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes when to use (get full record by various identifiers) and mentions response_mode verbosity levels. Lacks explicit when-not-to-use or comparison to all siblings, but context of sibling tools makes it clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint, idempotentHint) are reinforced by description detailing pagination, response fields (member_count, returned, truncated, next_offset, next_commands), and ambiguity resolution. No contradictions.
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?
Single, well-structured paragraph with clear sentences. Front-loads the main action, then details pagination and edge cases. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fully explains pagination, ambiguity handling, and response structure. Covers all necessary behaviors for an AI agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% parameters, but description adds meaning: group parameter examples, pagination behavior for limit/offset, and response_mode verbosity levels. Enhances understanding beyond schema.
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 verb 'Browse' and the resource 'HGNC gene group/family', with specific input options (numeric id or name). It distinguishes from siblings like get_gene which handles individual genes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit usage context: browse groups by id or name. It describes how to handle ambiguous names by returning candidates for re-call with an id. Lacks explicit when-not-to-use, but sibling names provide context differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only and idempotent. The description adds detail on return structure and suggests it as a discovery surface, but does not disclose rate limits or auth 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 front-loaded with purpose, efficiently details both detail modes, and provides a clear call to action. Every sentence is informative with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fully explains return contents for both detail levels and mentions alternative access. This is complete for a server capabilities tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with enum and default. The description adds semantic context by detailing what each detail level contains, going beyond the schema's short description.
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 tool returns the 'hgnc-link discovery surface' with a specific verb and resource. It distinguishes from sibling gene-focused tools by addressing server metadata.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises 'Call this first in a cold session' and provides alternative access methods (hgnc://tools / hgnc://capabilities). Detail levels are contrasted to guide selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the resolution cascade, individual miss behavior (marked unresolved/obsolete), and returned counts. No contradictions with annotations (readOnlyHint, idempotentHint, etc.).
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?
Three focused sentences with no redundancy. Front-loaded with purpose. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains return values (per-query results + counts) despite no output schema. Could briefly describe what each response_mode yields, but overall sufficiently complete for a batch read tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage, but description adds significant context: explains the cascade, batch safety, and that response_mode controls verbosity. Mentions signature for clarity.
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?
Description clearly states it resolves a batch of gene symbols/HGNC IDs (max 200) with the same cascade as resolve_symbol. It specifies per-query results and counts, distinguishing it from sibling tools like resolve_symbol.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for batch usage (max 200) and behavior on misses/withdrawals. Implicitly suggests using resolve_symbol for single queries, but lacks an explicit when-not statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already show readOnlyHint, idempotentHint, etc. The description adds beyond them by specifying FTS relevance-ranked search, return fields, and the nomenclature-only constraint, giving full behavioral context without contradiction.
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?
Three sentences, each earning its place: purpose, limitation, usage guidance. Front-loaded with key action and return format. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description specifies return fields and structure. Covers search behavior, limitations, and usage context. With sibling list and robust annotations, no important context is missing.
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 baseline is 3. The description reiterates parameter roles (e.g., query is free-text) and adds a signature line, but does not significantly extend parameter meaning beyond the schema.
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 'Free-text search over gene symbols, names, aliases, and previous symbols' with a specific verb and resource. It distinguishes from siblings by directing to resolve_symbol for exact matches and highlighting nomenclature-only scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool ('use this for partial names') and when to use alternatives ('use resolve_symbol for an exact symbol/id'). Also clarifies that descriptive queries only match nomenclature words, providing clear usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds that the tool reports status with no side effects and specifies the exact output fields and the fact that it takes no parameters, going beyond annotations.
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?
Two sentences plus a signature line. Extremely concise, with all key information front-loaded. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description enumerates all returned fields: built status, release date, gene/withdrawn counts, schema version, built time. This is complete for a diagnostic tool and aligns with the stated use case of confirming freshness or diagnosing errors.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters (0 params, schema coverage 100%). The description explicitly states 'Signature: get_hgnc_diagnostics()' confirming no arguments, which adds clarity beyond the empty schema.
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 tool reports local HGNC index status with specific fields (built status, release date, counts, schema version, built time). It distinguishes from sibling tools which focus on gene lookup and cross-references, not diagnostics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to confirm freshness or diagnose an unavailable-data error', providing clear context for when to use. Does not explicitly mention alternatives like get_server_capabilities, but the use case is well-defined.
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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