Server Quality Checklist

Tool Scores

• minionifyA
  3.9/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Description adds value beyond annotations by clarifying the transformation is 'lossy wordplay, not a real-language translation', which warns about semantic fidelity. Annotations already indicate read-only and non-destructive operations; this extra context improves 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?

  Description is two sentences, front-loaded with the core action, and contains no redundant information. Every word adds value.

  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?

  Given the tool's simplicity (2 parameters, output schema present), the description is sufficiently complete. It covers the nature of the transformation (lossy wordplay) and input constraints (short sentence). Output schema handles return value 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 description coverage is 100%, so baseline of 3 is appropriate. The description adds minimal parameter-specific context (e.g., 'short sentence' implies text length), but doesn't supplement the schema's parameter descriptions significantly.

  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 'creatively restyle[s] a short sentence or summary', which is a specific verb and resource. It distinguishes itself from sibling tools (chat, search, hunt) by focusing on single-sentence transformation, though it doesn't explicitly differentiate.

  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?

  Description implies usage for user-supplied short text ('short sentence or summary'), but provides no explicit guidance on when to use this tool versus sibling tools like minion_chat or minion_bun_hunt, nor any exclusions.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• minion_web_searchA
  4/5.0
  Behavior3/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that it performs a 'live web search' and returns a 'ready-to-display Minion verdict,' but does not reveal additional behavioral details like rate limits or result fallback logic. With annotations covering the core traits, the description provides moderate added value.

  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 only two sentences long. The first sentence states the core purpose, and the second provides usage guidance. No unnecessary words or repetition. Every sentence contributes meaning.

  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?

  The description covers purpose, usage context, and hints at the output format. Given that there is an output schema (present but not shown), the description does not need to detail return values. It is sufficient for an agent to understand when and how to invoke the tool, though a bit more detail on the verdict structure could enhance completeness.

  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 has 100% description coverage for all parameters, so the schema already documents each parameter. The description does not add extra semantic context beyond the schema. Per calibration, baseline is 3 when schema coverage is high, and no additional value is provided here.

  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 performs live web searches and returns a formatted verdict with ranked sources. It also distinguishes itself from sibling tools by directing users to use it instead of a separate host search tool, though siblings (minionify, minion_chat, minion_bun_hunt) are unrelated to search.

  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 says to use this tool for online lookups, recommendations, and shopping requests instead of a separate host search tool. It provides clear context but does not specify when not to use it, though the positive use cases are well defined.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• minion_chatA
  4.3/5.0
  Behavior4/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds context that the persona is offline and does not browse or execute instructions, which aligns with annotations and provides additional behavioral clarity.

  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 at two sentences, front-loaded with the key action, and contains no superfluous information. Every sentence adds value.

  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?

  Given the tool's simplicity (character chat), the description covers all necessary aspects: mode of interaction, output nature (translation), and boundary (offline). No obvious 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?

  Schema coverage is 100%, so the parameters are well-documented. The description adds flavor (e.g., 'banana reactions') but no additional semantic detail beyond what the schema provides. 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 states the tool is for talking to a Minion-style helper with specific behavior (Minionese chatter, banana reactions, translation). It distinguishes from siblings like minion_web_search by noting the offline persona does not browse or execute instructions.

  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 implies when to use (chat with a character) and explicitly states when not to use (for browsing or tasks), providing guidance on alternatives. However, it could be more explicit about preferring minionify or other tools for specific use cases.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

• minion_bun_huntA
  4.5/5.0
  Behavior5/5

  Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

  Annotations already mark it as read-only and open-world. The description adds significant behavioral context: it disambiguates 'buns' to food meanings, inspects product evidence, scores relevance and juiciness, and selects a citation-backed winner. This goes beyond annotations to explain the tool's internal logic.

  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, front-loaded sentence that efficiently conveys the entire tool workflow. Every clause adds value, with 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?

  Given tool complexity (multi-step search, scoring, ranking) and presence of an output schema, the description covers the high-level flow adequately. It mentions key steps like discovery, rejection of irrelevant meanings, scoring, and crowning a winner, providing enough context for an 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 has 100% coverage with descriptions for all 6 parameters. The description does not add parameter-specific semantics beyond what is in the schema, such as the default request or the provider backend. Baseline score of 3 is appropriate as the schema already explains parameters well.

  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's specific purpose: discovering food buns, rejecting irrelevant meanings, inspecting evidence, scoring multiple attributes (juiciness, orderability, proof), and crowning a winner. It uses a specific verb (discover, crown) and differentiates from sibling tools like minion_web_search (general search) and minion_chat (chat).

  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 indicates it is for a specific demo ('Run the gold Minion MCP demo') and implies usage for finding the juiciest buns. However, it does not explicitly state when to use this tool vs alternatives or when not to use it, missing clear exclusion criteria.

  Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.