Minuet

Official

by minuetai

Overview Schema Related Servers Score Discussions

Python

Remote

Server Quality Checklist

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Latest release: v0.1.1
Disambiguation5/5
Each tool has a clearly distinct purpose: agent details, relationships, hubs, stats, ecosystems, recent relationships, graph, and search. No overlap in functionality.
Naming Consistency5/5
All tool names follow a consistent snake_case verb_noun pattern (e.g., get_agent, search_agents), with no deviations or mixed conventions.
Tool Count5/5
8 tools is appropriate for the domain of querying agent relationships and network statistics, covering all essential functionalities without excess or deficiency.
Completeness5/5
The tool surface provides comprehensive read-only coverage: individual lookups, relationship listing, top hubs, stats, ecosystems, recent activity, full graph, and search. No obvious gaps for this query-focused server.
Average 3.8/5 across 8 of 8 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on April 23, 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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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, the description must disclose behavioral traits. It only states it returns recent relationships, but does not specify ordering, safety (read-only vs destructive), or any side effects. This is insufficient for reliable agent decision-making.
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 short and front-loaded with the main purpose. However, it uses a structured 'Args' format that could be streamlined. It is efficient but not maximally concise.
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 simplicity and the presence of an output schema (not shown), the description is minimally complete. It lacks explanation of what a 'relationship' is and any prerequisites. For a simple list tool, this is adequate but leaves gaps.
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 meaning to the 'limit' parameter beyond the schema (which only provides default and type), stating it controls the maximum number of relationships. However, with 0% schema coverage, it should provide more detail, such as range constraints or behavior if omitted.
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 returns 'the most recently created relationships', which is a specific verb and resource. However, it does not differentiate from sibling tools like get_agent_relationships or search_agents, which could also return relationship data.
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?
There is no guidance on when to use this tool versus alternatives. It does not mention prerequisites, contexts, or exclusions, leaving the agent to infer usage from 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 must fully disclose behavior. It only mentions returning a graph with an optional filter, but does not state if the operation is read-only, authentication requirements, or any side effects. The absence of such details leaves the agent underinformed.
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: one sentence for the main purpose, followed by a three-line parameter explanation. Every sentence adds value, and the most important information is front-loaded.
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?
The tool has a moderate complexity (graph return, one parameter) and an output schema (content unknown). The description covers the parameter and basic output type, but omits details about graph structure, node/edge format, and behavioral aspects like caching or pagination. It is minimally adequate but not thoroughly complete.
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?
The input schema has 0% coverage for parameter descriptions, but the description explains 'min_connections' in detail: 'Filter out agents with fewer than this many relationships from the returned edge list (default 0 = no filter).' This adds meaning beyond the schema, effectively compensating for the lack of schema 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 clearly states the purpose: 'Return the full set of relationships as a graph.' This uses a specific verb and resource, distinguishing it from siblings like get_agent_relationships (likely for a single agent) and get_recent_relationships (limited scope).
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 does not provide any guidance on when to use this tool versus alternatives like get_agent_relationships or search_agents. It lacks explicit context about the trade-offs or use cases.
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 provided, so description carries full burden. States 'Fetch', implying read-only, but no mention of authentication, rate limits, or response characteristics. Adequate but minimal.
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 an ARGS section. Every sentence adds value; no filler. Front-loaded with 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?
Given one parameter and an output schema, description covers the key format. Could mention that relationships are embedded in the response, but adequately complete for this simple fetch 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 description coverage is 0%, so description must compensate. It adds format 'chainId:agentId' with example, which is valuable beyond the schema's type-only definition.
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?
Explicit verb 'Fetch' and resource 'full details for a specific agent' with clear scope 'including its Minuet relationships'. This distinguishes it from sibling get_agent_relationships, which likely returns only relationships.
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 or when to choose alternatives. Provides the required parameter format but no context on appropriate use cases.
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 should disclose behavioral traits. It mentions the parameters and their meanings but does not discuss query behavior when null, case sensitivity, or result structure. Some context is added, 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?
The description is concise, with a clear purpose sentence followed by parameter explanations. No unnecessary words or repetition.
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 an output schema exists, the description does not need to detail return values. It covers the essential information for a simple search tool with two optional parameters, though it could mention that results are limited to indexed 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 0%, so the description must add meaning. It explains query as a substring match against agent name and limit as maximum agents returned (with default), providing useful context 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 it searches indexed ERC-8004 agents, using a specific verb and resource. This distinguishes it from siblings like get_agent (single agent) and get_hub_agents (hub-specific).
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_agent or get_hub_agents. The description does not mention prerequisites or contextual cues for 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 provided, so the description carries full burden. It only states 'List relationships' implying a read operation, but lacks disclosure on safety, authorization needs, rate limits, or any 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and well-structured: a single-line summary followed by a clear Args section. Every sentence is essential with no redundant information.
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 only 2 parameters, no annotations, and an existing output schema, the description covers the core functionality. However, it could benefit from additional context on behavioral transparency and usage guidance relative to siblings.
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 schema properties have no descriptions (coverage 0%), but the tool description explicitly explains the agent_id format (canonical chainId:agentId) and direction values (incoming, outgoing, both) with a default. This adds crucial meaning beyond the raw 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 'List relationships for a specific agent.' and specifies the agent_id format and direction options. This contrasts with siblings like get_relationship_graph (graphical) and get_recent_relationships (filtered), providing a distinct purpose.
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 through parameter examples but does not explicitly state when to use this tool over siblings like get_relationship_graph or get_recent_relationships, nor does it include when-not scenarios.
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 bears full burden but only states return of most-connected agents. No disclosure of pagination, sorting, performance, or other behavioral traits.
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 short, front-loaded sentences covering purpose and usage, plus a clear Args section. No wasted words.
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?
Adequately complete for a simple tool with one parameter and an output schema; no need to describe return values. Could mention edge cases.
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 description coverage is 0%, but the description adds clear meaning for the 'limit' parameter: 'Maximum number of hubs to return (default 10).'
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?
Clearly states it returns the most-connected agents in the Minuet relationship graph, distinct from siblings like get_agent (single agent) or get_relationship_graph (entire graph).
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 usefulness for discovering which agents work together, providing clear context on when to use. Lacks explicit guidance on when not to use or alternatives.
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 carries full burden. It explains the result (owners with multiple agents) and defines ecosystem criteria, but does not disclose authorization needs, side effects, or rate limits. The read-only nature is implied by the 'get' prefix but 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 extremely concise: three short sentences and an Args section. The purpose is front-loaded, and every line earns its place. No redundant information.
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's simplicity (one optional parameter, output schema exists), the description covers purpose, parameter, and a usage hint. It does not mention error cases or prerequisites, but overall is sufficiently complete for an agent to select and invoke correctly.
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 input schema has 0% description coverage, but the description's Args section fully explains the 'limit' parameter with its purpose and default value. This compensates entirely for the schema's lack of 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 clearly states the tool returns owners operating multiple connected agents, defines 'ecosystem', and distinguishes from sibling tools that focus on individual agents or relationships. The verb 'Return' and specific resource ('owners with multiple agents') make 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'Useful for finding multi-agent teams', providing a clear use case. However, it does not mention when to avoid this tool or compare it with siblings like 'get_agent_relationships' or 'search_agents', which could further guide selection.
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 provided, but the description honestly discloses that it returns aggregate stats, not individual data, and lists the specific statistics. No hidden behaviors or 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 states purpose and key resource, second lists details. Front-loaded, 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?
For a parameterless tool with no annotations and an output schema (implied by context), the description fully covers what the tool does and what it returns. No gaps.
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?
Input schema has no parameters (0), so schema coverage is 100%. Description adds meaning by specifying the exact statistics returned, going beyond what an empty schema provides.
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?
Clearly states it returns aggregate statistics about the Minuet relationship graph and lists specific items (totals for relationships, agents, named agents, verified vs inferred status, top relationship types). Distinct from siblings like get_agent (specific agent) and get_relationship_graph (graph structure).
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?
Implied usage is when overall network statistics are needed. No explicit when-not-to-use or alternatives, but siblings are sufficiently different that the tool's role is clear.
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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