trust-mcp
Server Quality Checklist
Latest release: v1.2.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: lookup retrieves trust scores, register adds an agent, review submits a review, and list enumerates agents. No overlap or ambiguity exists.
Naming Consistency5/5All tools follow a consistent 'trust_verb' pattern using snake_case. The verb is always a clear action, making the API predictable and easy to navigate.
Tool Count5/5With only 4 tools, the server is tightly scoped to its purpose of managing trust scores and reviews. Each tool contributes to a clear workflow without redundancy.
Completeness4/5The core lifecycle is covered: register, look up, review, and list. Minor gaps include no tool to update or delete a review or modify agent registration, but these are not essential for a simple trust registry.
Average 3.8/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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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 are provided, so the description must carry the full burden of disclosing behavioral traits. It only mentions 'Free registration, instant trust score' and does not disclose that registration is a side-effecting operation (e.g., creating a record), any data retention implications, or required permissions. This is a significant gap for a mutation-like tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that starts with the primary verb and immediately conveys the core action and key benefits. There is no extraneous information, making it highly concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only three parameters and no output schema, so the description is mostly adequate. However, it lacks any disclosure of side effects, return values, or post-registration behavior, which would be helpful given the absence of annotations and output schema. It is the minimum viable description but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides full parameter descriptions for all three parameters (name, contact, description), so the description does not need to add parameter semantics. The baseline of 3 applies because the schema covers parameter meaning fully, and the description adds no additional context beyond that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does 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 ('Register') and resource ('trust registry'), making it obvious that this is for self-registration. It distinguishes itself from sibling tools like trust_lookup, trust_review, and trust_list by indicating a write/creation action rather than read/review actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for use: it is for registering oneself in the trust registry, with the added benefits of free registration and instant trust score. It does not explicitly name alternatives or state when not to use it, but the verb and resource make the intended use unambiguous relative to sibling tools.
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 the behavioral burden. It states the core behavior (listing all agents with trust scores) and mentions pagination, but it does not disclose return format, sorting, or whether pagination is offset-based. The description is not misleading but leaves some behavioral details unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence that states purpose and pagination support. Every word earns its place, with no filler or redundant detail beyond a useful clarification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with low parameter count and full schema coverage, the description covers the purpose and behavior adequately. The lack of an output schema is mitigated by the clear mention of what is returned (agents with trust scores). It does not need to list every pagination detail because the schema provides that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters (page and limit) with descriptions, and schema coverage is 100%. The description only repeats the pagination concept without adding new meaning, so it stays at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action (List) and resource (all registered agents with their trust scores), which distinguishes it from the sibling tools trust_lookup, trust_register, and trust_review. It immediately signals this is the 'list all' operation among the trust-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the verb 'List' and the resource scope, and the pagination note offers some context. However, there is no explicit guidance on when to choose this over trust_lookup or any exclusions or prerequisites.
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 the full burden. It discloses one important behavior: reviews with proof-of-payment are marked as verified. However, it does not mention side effects (e.g., permanence, editability, authentication requirements) or what happens on submission, so transparency is partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that front-loads the purpose and adds a key behavioral detail. No wasted words or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a write operation with no annotations and no output schema. The description does not mention return values, prerequisites (e.g., whether the agent must be registered with trust_register), or how the review is linked to a specific transaction. This leaves significant gaps for an agent deciding whether and how to invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and notable parameter descriptions already explain the verification effect of proof_of_payment. The description adds no new parameter semantics beyond restating that proof-of-payment affects verification status, which the schema already covers.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Submit') and resource ('a review for an agent'), along with a clear context ('after a transaction'). This distinguishes it from siblings like trust_lookup, trust_register, and trust_list, which are not write/review operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides a clear usage context: 'after a transaction'. This tells the agent when to invoke the tool. It does not explicitly mention alternatives or exclusions, but the sibling names suggest when other tools might be appropriate, so the guidance is adequate though not exhaustive.
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 the burden of behavioral disclosure. It reveals the return structure (score, tier, verification details), which is helpful, but does not comment on side effects (though a lookup is presumably read-only), permissions, or error behavior. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, front-loaded with the action, and includes key details without waste. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one parameter and no output schema, the description adequately covers purpose, usage, and return values. It lacks details about possible failure modes or verification specifics, but is complete enough for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter (agent_id), so the schema fully documents it. The tool description does not add additional parameter semantics beyond what the schema provides, meriting the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb ('Look up') and resource ('agent's trust score'), and adds usage context ('before transacting'). It is distinct from sibling tools (trust_register, trust_review, trust_list) which imply different actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context ('before transacting') and implies this tool is for lookup, but does not explicitly mention when not to use it or name alternatives. It is clear enough for an agent to choose this over siblings.
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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