Server Quality Checklist

Tool Scores

• get_conversationB
  3.3/5.0
  Behavior3/5

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

  No annotations provided, so description solely informs behavior. It discloses search order (personal memory then library) but omits other traits like idempotency, error handling, or what happens if conv_id is not found.

  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 with 12 words, no filler. Action verb first, efficient and 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?

  Given low complexity and presence of output schema, description covers basic operation but misses detail like uniqueness or encoding of conv_id. Gaps remain due to no annotations.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 0%, yet description only restates 'by conv_id' without adding format, examples, or constraints. The parameter meaning is only trivially extended.

  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 retrieves a full conversation thread using a conv_id, and specifies a two-step search order. However, it does not explicitly differentiate from sibling tools like get_conversation_summary.

  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 (need full thread by ID) and provides search order, but lacks explicit when-not-to-use scenarios or direct comparison to alternatives like list_recent_conversations.

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

• list_project_conversationsA
  4/5.0
  Behavior3/5

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

  No annotations provided, so description carries full burden. It discloses substring matching and parameters but omits ordering, pagination, or whether conversations are read-only. Some key behavioral aspects are missing.

  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 one-line purpose, brief matching detail, and a clean args list. Every sentence adds value, and the structure is logically 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 the existence of an output schema (not detailed here), the description adequately covers the tool's function, matching logic, and parameters. Minor gaps like missing ordering or error handling are acceptable for a list 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?

  With 0% schema description coverage, the description compensates by explaining each parameter: project as substring, days as look-back window, limit as max count. It adds 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 the tool 'returns recent conversations scoped to a project or workspace' with substring matching on title. It distinguishes from sibling tools like 'list_recent_conversations' by emphasizing project/workspace scope.

  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 (to find conversations by project substring) but does not explicitly state when not to use or compare with alternatives. The sibling tools are not referenced, leaving the agent to infer context.

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

• get_conversation_summaryA
  4.1/5.0
  Behavior3/5

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

  No annotations, so description bears full burden. Describes read-like operation and return fields, but does not explicitly state it's read-only or discuss error cases, rate limits, or side effects. 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.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Concise two paragraphs, first summarizing purpose and return fields, second listing args. No unnecessary words. Could be more structured but effective.

  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 return fields, args, and usage context. Output schema exists, so return details are fine. Missing info on limits or error handling, but sufficient for typical use.

  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 zero description coverage, so description must compensate. It adds meaning to conv_id (source) and max_messages (split between start and end, default 12). This goes beyond schema information.

  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 gets metadata and a bounded excerpt, not full transcript, distinguishing from get_conversation. The verb 'Get' and resource 'conversation summary' are specific.

  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 when to use (compact excerpt without full transcript) and where to get conv_id (search_personal_memory, list_recent_conversations). Lacks explicit when-not-to-use but contrast with siblings is clear.

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

• list_recent_conversationsA
  4.1/5.0
  Behavior3/5

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

  The description discloses the ordering (recency), output format (row headers with fields), and parameters. However, with no annotations provided, it does not fully disclose behavioral traits such as whether this is a read-only operation, any rate limits, or error handling. For a read tool, this is adequate but not comprehensive.

  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 and well-structured: a one-sentence summary of purpose, usage guidance, output format preview, and a bullet list of parameters with defaults and examples. Every sentence serves a purpose, and key information 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 that an output schema exists, the description is fairly complete: it covers purpose, usage cues, parameter details, and output format. It does not discuss potential edge cases (e.g., no results, maximum days) or error handling, but these are minor gaps for a simple list 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 description coverage is 0%, so the description carries the full burden for parameter meaning. It provides clear explanations for all four parameters: 'days' (look-back window, default 2), 'limit' (max conversations, default 20), 'platform' (filter with examples), and 'project' (substring match with examples). This adds significant value beyond the schema alone.

  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 that the tool returns conversations ordered by recency, not semantic similarity. It provides a specific verb ('Return') and a resource ('conversations'), and implicitly distinguishes from sibling tools like search_ghost_memory by clarifying it is not semantic search. However, it does not explicitly differentiate from other list tools like list_project_conversations.

  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 advises when to use the tool: 'Use this when the user asks for recent conversations...' with examples including Japanese phrases. It does not specify when not to use it or mention alternatives, but provides clear context for its intended use case.

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

• search_ghost_memoryA
  4.1/5.0
  Behavior5/5

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

  No annotations provided, so description carries full burden. It discloses ranking formula, the self-tuning loop via bump_activation (side effect), and security details about SECURITY DEFINER and shared-restricted allowlist. This is comprehensive behavioral disclosure.

  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?

  Well-structured with clear sections: purpose, security warning, ranking formula, side effect. Front-loaded core usage. However, the ranking formula is detailed and may be more than necessary for an agent to select/invoke the tool correctly.

  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?

  For a tool with 5 parameters and no schema descriptions, the description covers overall behavior, ranking, side effect, and security. But missing explanations for n_results, expand_links, and include_restricted limit completeness. Output schema exists, so return values are not needed.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 0%, so description must explain all 5 parameters. It only explains the query parameter (empty vs. non-empty) and implicitly current_project via security warning. n_results, expand_links, and include_restricted are not described. The ranking formula is given but not tied to parameters.

  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 the tool searches cross-project agent ghost memories, differentiating empty query (list top-ranked) from non-empty query (hybrid search). The verb 'search' and resource 'ghost memory' are specific, and sibling tools (conversations/diaries) are distinct.

  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 context for empty vs. non-empty query usage and security caveats about current_project not being server-verified. Lacks explicit alternatives among siblings, but the purpose is so distinct that siblings are clearly different.

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

• get_diaryA
  4.8/5.0
  Behavior4/5

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

  No annotations provided, so description carries full burden. It describes the diary layer, entry frequency, and return behavior. Lacks explicit statement about non-destructiveness, but context implies read-only. Minor gap for full 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?

  Highly concise: one sentence states purpose, paragraph explains distinct layer, then Args section. No fluff, 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?

  Given two parameters and existence of output schema, description fully covers tool's behavior, usage, and parameters. Sibling tools are distinct, so no missing context.

  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 coverage is 0%, but description adds full meaning: date values ('latest' or YYYY-MM-DD), n meaning (number of recent entries when date='latest', default 1, max 14). Complements 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 reads the agent's daily first-person diary, distinguishing it from conversation tools by noting the diary is a separate layer not surfaced by search_personal_memory.

  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 explains when to use (to read the diary itself) and when not (since search_personal_memory does not surface it). Arg section details parameter usage: date as 'latest' or specific day, n for count with max 14.

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