skosmos-mcp

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.1.0
Disambiguation3/5
Most tools have distinct purposes, but 'get_concept_label' and 'labels' overlap significantly, both retrieving labels for a concept URI. Additionally, 'broader_concepts' and 'traverse_concepts' can be confused since traverse supports broader traversal. This creates some ambiguity for an agent.
Naming Consistency4/5
Tool names mostly follow a consistent verb_noun pattern (e.g., list_vocabularies, get_concept, resolve_label). However, 'autocomplete' is a single word and 'concept_path' is noun_noun, breaking the pattern. The overall structure is clear despite these minor deviations.
Tool Count5/5
With 13 tools, the server is well-scoped for SKOS vocabulary browsing. It covers listing, searching, detail retrieval, and hierarchy traversal without being overwhelming. The count is appropriate for its purpose.
Completeness4/5
The tool surface covers core SKOS operations: vocabulary listing, concept details, labels, hierarchy traversal (broader, narrower, related), and search (autocomplete, full-text, label resolution). Missing are concept creation/modification (likely out of scope) and some non-core features like concept collections, but the browsing workflow is complete.
Average 3.3/5 across 13 of 13 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 45 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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?
No annotations provided, so description carries full burden. It only hints at output content but lacks details on read-only nature, authorization, performance, or side effects.
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?
Single sentence with clear verb and resource. Efficiently conveys core purpose without superfluous text.
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 no output schema and multiple sibling tools, description lacks detail on response structure and does not help agent decide when to prefer this aggregated tool over specific relationship tools.
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 coverage is 100% with descriptions for all parameters. Description does not add meaning beyond schema, so 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?
Description clearly states the tool retrieves concept details including relationships. It distinguishes from siblings by implying aggregation, but does not explicitly differentiate from narrower, broader, related concepts tools.
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?
No guidance on when to use this tool vs siblings like broader_concepts, narrower_concepts, etc. The description is purely descriptive and does not provide selection criteria.
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, the description carries the full burden. It mentions 'including top concepts' but does not disclose whether the tool is read-only, required permissions, or any side effects. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that communicates the core function without waste, though it could benefit from slightly more detail without losing conciseness.
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?
Lacking output schema and annotations, the description should provide more context on return format, error handling, or usage scenarios. It mentions 'top concepts' but is otherwise incomplete.
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 coverage is 100%, so the schema already describes both parameters. The description adds no additional meaning beyond what is in the schema, earning the baseline score.
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 it gets details of a specific vocabulary including top concepts, distinguishing it from siblings like list_vocabularies and get_concept, but 'details' is somewhat vague.
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?
No guidance on when to use this tool versus alternatives, such as list_vocabularies for listing all vocabularies or get_concept for a specific concept. The description does not provide exclusions or 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 bears full responsibility. It only states 'List all available vocabularies', omitting behavioral traits such as read-only nature, authentication requirements, or output format. The description adds minimal transparency beyond the basic operation.
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?
A single sentence of 7 words that is front-loaded with the purpose. Every word is necessary and there is no 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?
The tool is simple, but with no output schema and no annotations, the description should explain what the output contains (e.g., vocabulary IDs, labels) or whether there is pagination. The current description is too sparse to be fully self-contained.
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 coverage is 100% and the schema already describes the 'lang' parameter. The description does not add any additional meaning or usage context for the parameter, so it meets the baseline but provides no extra value.
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 'List' and resource 'all available vocabularies' in the Skosmos instance. It is specific enough to distinguish from sibling tools which are mostly about individual concepts or searches, though it does not explicitly differentiate from 'get_vocabulary'.
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?
No guidance on when to use this tool versus alternatives like 'get_vocabulary' or 'search_concepts'. It does not mention prerequisites, use cases, 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, the description should carry behavioral details, but it only states the function. Missing information on case sensitivity, exact vs fuzzy matching, multiple matches, or response format.
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. Every part is necessary for stating the core 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?
Given the tool's simplicity and lack of output schema, the description is too sparse. It omits important context like what 'resolve' entails (exact match? returns multiple concepts?), which would help the agent anticipate behavior.
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 coverage is 100%, and the description adds minimal value beyond repeating parameter names. The baseline of 3 is appropriate because the schema already documents each parameter's meaning.
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 'resolve' and the resource 'a label text to concepts in a vocabulary', making the tool's purpose specific. However, it does not explicitly differentiate it from siblings like 'search_concepts' or 'autocomplete', though the action is distinct enough.
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?
No guidance is provided on when to use this tool versus its many siblings (e.g., search_concepts, autocomplete, get_concept). There are no when-not or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions BFS algorithm and depth limitation, adding behavioral context beyond a generic 'get related concepts'. However, with no annotations provided, it fails to disclose whether the operation is read-only, how cycles are handled, or what the output format is.
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 a single concise sentence with no unnecessary words. It efficiently conveys the core operation, though it could benefit from additional structure to separate input/output details.
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 graph traversal tool, the description is insufficient. It does not explain the return value, result order, limits on results, or error conditions. The absence of an output schema increases the need for description completeness, which is not met.
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 already describes all 4 parameters with clear definitions (100% coverage). The description adds the algorithmic detail of BFS but does not augment parameter meaning beyond what the schema provides, so baseline 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 performs a BFS traversal of related concepts with depth control. However, it does not distinguish this from sibling tools like 'traverse_concepts', 'broader_concepts', or 'narrower_concepts', which may overlap in functionality.
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?
No guidance is provided on when to use this tool versus alternatives. Siblings such as 'broader_concepts' and 'narrower_concepts' suggest more specific traversals, but the description does not clarify when 'related_concepts' is appropriate or when to use other traversal 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 full burden for behavioral disclosure. It only states the basic operation, omitting important details such as whether the tool is read-only, the format of suggestions, or any side effects. The autocomplete nature implies a read operation, but this is not explicit.
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, well-formed sentence that conveys the core purpose with no unnecessary words. It is ideally concise.
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 absence of an output schema, the description should provide some indication of what the tool returns (e.g., list of suggestions). It fails to do so, leaving a gap in contextual completeness for a tool with 4 parameters and no output specification.
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 coverage is 100%, and the input schema already describes each parameter sufficiently. The description adds no additional context or examples, meeting the baseline expectation.
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 action ('autocomplete'), the resource ('concept labels'), and the method ('by prefix'), making the purpose immediately understandable. It precisely matches the tool's name.
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 like 'search_concepts' or 'resolve_label'. There is no mention of context, 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?
No annotations provided; description only specifies BFS traversal but omits details about side effects, read-only nature, pagination, or output format. This leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with key action (BFS traversal) and specifies relationship types. No extraneous text.
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?
Despite good schema coverage, the description lacks details on return values, traversal order, or limits. For a traversal tool with no output schema, more context is needed to set expectations.
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 coverage is 100%, so parameters are well-documented structurally. Description adds context that the tool uses a mix of relationships, but does not explain parameter constraints or advanced usage 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?
Description clearly states it performs BFS traversal over concept relationships (broader, narrower, related). This distinguishes it from siblings like broader_concepts which only handle one relationship type.
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?
No guidance on when to use this tool versus alternatives such as broader_concepts or narrower_concepts. The description does not mention scenarios where a mixed traversal is preferable.
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 provided, so description carries full burden. States operation is read-only ('Get'), but omits details about returned format, error handling, required permissions, or behavior for missing URIs.
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 sentence, front-loaded with key information, no redundant or superfluous content.
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?
No output schema and rich sibling set (12 tools). Description does not specify return format (e.g., object or array) or handle edge cases (e.g., missing language code), leaving significant gaps for 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?
Schema coverage is 100% with descriptions for all 3 parameters. Description adds minimal context beyond schema (e.g., 'for a concept URI' aligns with 'uri' param), but does not enrich understanding of 'lang' or 'vocabulary' usage.
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 identifies the verb 'Get' and the resource 'all labels (prefLabel, altLabel, hiddenLabel) for a concept URI'. It distinguishes from siblings like 'get_concept' (gets concept object) and 'resolve_label' (resolves label to concept).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing labels for a concept URI, but does not provide explicit when-to-use/when-not-to-use guidance or differentiate from 12 sibling tools like 'labels' or 'get_concept'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the traversal algorithm (BFS), scope (narrower concepts), and depth parameter. However, it omits behavior when depth is omitted (depth is optional in schema), return format, pagination, or performance considerations. Adequate but not thorough.
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?
Description is a single, front-loaded sentence with no extraneous words. It efficiently conveys the core action and key constraints.
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 4 parameters, no output schema, and no annotations, the description is incomplete. It lacks details on optional behavior (depth), return structure, edge cases, or usage prerequisites. The agent may struggle to use this tool effectively without additional documentation.
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 coverage is 100%, so baseline 3. The description adds the 'BFS traversal' context but does not explain parameter interplay or formatting beyond what the schema provides. No extra semantic enrichment, so score remains at baseline.
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 'BFS traversal of narrower (child) concepts down to a specified depth', specifying the algorithm (BFS), relationship direction (narrower/child), and depth limitation. It distinguishes from siblings like broader_concepts and related_concepts, making the purpose unambiguous.
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?
No explicit guidance on when to use this tool versus alternatives. While the description implies use for fetching child concept hierarchies, it does not mention when to avoid it (e.g., for direct children only, use get_concept instead) or contrast with traverse_concepts. The agent must infer context from sibling names.
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 provided. Description only says 'full-text search' and does not disclose behavioral traits such as pagination behavior, result format, sorting, or field search scope. Schema parameters hint at pagination but description adds no 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?
Single sentence, no fluff, front-loaded with the essential purpose. Every word earns its place.
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?
With 5 parameters including pagination and no output schema, the description should explain return format or behavior. It only states purpose. Agent lacks info on response structure or how pagination works.
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 coverage is 100%, baseline is 3. Description does not add any parameter-level information beyond what the schema provides. It does not clarify usage of 'vocabulary' or 'offset'/'maxhits' semantics.
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 verb 'search', resource 'concepts', and scope 'across one or all vocabularies'. Distinguishes from siblings like autocomplete (prefix search) and get_concept (single concept retrieval).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage: use for full-text search across concepts. No explicit when-not-to-use or mention of alternatives like autocomplete or concept_path. Guidance is minimal but not misleading.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must disclose behaviors. It mentions 'via broader transitive relations' indicating upward traversal, but does not specify edge cases (e.g., no broader concepts), return format, or potential errors.
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, concise, front-loaded sentence with no wasted words.
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?
With no output schema, the description should clarify the return value (e.g., list of URIs or labels). It only mentions 'hierarchy path', leaving format ambiguous. Parameters are well-covered but no context on ordering or defaults.
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?
Input schema covers 100% of parameters with descriptions. The tool description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
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 specifies the action: 'Get the hierarchy path from a concept to its root via broader transitive relations'. It distinguishes from siblings like 'broader_concepts' (which likely returns immediate broader concepts) by emphasizing the transitive path to root.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (to get the full hierarchy path), but does not explicitly state when not to use it or mention alternatives among the siblings like 'broader_concepts' for immediate parents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It reveals the use of BFS algorithm and depth limit, but omits performance traits, edge case behavior (e.g., missing concepts, circular references), or result format.
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 sentence of 10 words, zero waste, and front-loads the core information: algorithm, relationship, and depth constraint. Every word is meaningful.
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 the tool complexity (graph traversal) and good schema coverage, the description is adequate for core functionality. However, it lacks details on return format (e.g., list of URIs, labels) or error conditions, which could be added without being excessive. No output schema exists 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 coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning beyond the overall purpose; it does not clarify parameter relationships or constraints beyond what is in 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 the tool performs BFS traversal of broader (parent) concepts up to a specified depth, with specific verb ('traversal'), resource ('broader concepts'), and scope ('up to a specified depth'). This distinguishes it from siblings like 'narrower_concepts' and 'related_concepts'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for hierarchical parent traversal but does not explicitly state when to use it over alternatives (e.g., 'traverse_concepts' for general traversal, 'narrower_concepts' for children). No scenarios or exclusions are provided.
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?
No annotations exist, but the description clearly indicates a read-only operation ('Get') with no side effects. It does not contradict annotations, and the behavior is transparent for a retrieval tool.
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?
A single, front-loaded sentence with no filler words. Every word is necessary and contributes to understanding the tool's 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?
For a simple retrieval tool with 3 well-documented parameters and no output schema, the description is adequate. It could optionally mention the return format, but this is not critical given the clarity of the operation.
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%, providing baseline of 3. The description adds meaning by explicitly linking 'uri' and 'vocabulary' as context, which goes beyond the schema's individual parameter descriptions.
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 uses a specific verb 'Get' and resource 'labels' with context 'for a concept URI in a vocabulary', clearly distinguishing it from sibling tools like 'get_concept_label' which likely returns a single label.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (retrieve labels for a concept URI), but provides no guidance on alternatives like 'resolve_label' or when not to use this tool.
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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