Server Quality Checklist

Tool Scores

• datacore_ingestC
  2.4/5.0
  Behavior1/5

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

  With no annotations provided, the description bears full responsibility for behavioral traits, but it only states the function without revealing side effects, authentication needs, or error conditions. This is insufficient for safe invocation.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

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

  The description is a single sentence with no wasted words, which is concise, but it sacrifices necessary detail. It is appropriately front-loaded but too brief to be genuinely helpful.

  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 and annotations, the description should compensate with richer context. It fails to explain the ingestion process, return value, or how it relates to sibling tools, leaving significant gaps.

  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 description coverage is only 33% (only 'content' has a description). The tool description does not elaborate on 'title' or 'tags', nor does it add meaning beyond the schema. For a low-coverage situation, more explanation was expected.

  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 'Ingest' and the resource 'text content as a knowledge note', which distinguishes it from siblings like 'datacore_search' or 'datacore_status'. However, it does not specify the exact outcome (e.g., storing or indexing), preventing a full clarity score.

  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 'datacore_capture' or prerequisites. The description provides no context for decision-making.

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

• datacore_searchB
  3.2/5.0
  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 mentions keyword search, but the schema includes a semantic method and a scope filter, which are not described. It also does not state side effects (e.g., read-only) 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 sentence that gets straight to the point. No wasted words and front-loaded with the core purpose.

  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 has 4 parameters (including optional scope and method) and no output schema, the description is too brief. It omits details like pagination, default scope, and return structure, leaving significant gaps for agent usage.

  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 high (75%), so baseline 3 is appropriate. The description adds no extra meaning beyond what the schema already provides for parameters like 'query' and 'limit'.

  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 verb 'Search' and the resources 'journal entries and knowledge notes', along with the method 'by keyword'. This fully distinguishes it from sibling tools like datacore_capture or datacore_status which have different purposes.

  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, nor are there any exclusions or prerequisites. The description merely states what it does without context.

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

• datacore_captureA
  3.5/5.0
  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 the basic function and proactive intent, omitting side effects, authentication needs, rate limits, or what the tool returns. The agent lacks context on outcomes like confirmation or storage.

  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 precisely describe the function and usage context without any redundant or verbose content. Front-loads the core action and then provides proactive guidance.

  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 4 parameters and no output schema, the description is adequate but incomplete. It does not clarify the difference between journal and knowledge entries, optionality of tags, or the output after capture. More detail would improve 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?

  The schema covers 75% of parameters with descriptions. The description adds context that 'journal' and 'knowledge' are options for the type parameter, but otherwise adds no meaning beyond the schema. This meets the baseline for high coverage.

  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 captures 'a journal entry or knowledge note,' specifying the resource type. It further guides proactive use for recording important decisions, meetings, and events, distinguishing it from sibling tools like search and ingest.

  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 suggests proactive use for important events but does not explicitly state when not to use the tool or mention alternatives like datacore_search for retrieval. The guidance is implied, not definitive.

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

• datacore_dateA
  3.8/5.0
  Behavior3/5

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

  No annotations provided, so description carries full burden. Lists operations but does not disclose error behavior, return formats beyond 'today's date', auth needs, or limitations. 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?

  Two sentences, no wasted words. First sentence is an imperative call to action; second sentence lists capabilities. Front-loaded and efficient.

  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?

  Missing details on return values for most operations (e.g., what does 'dow' return?). No output schema, so description should clarify; it only specifies 'today' returns date+dow. Incomplete for full usage.

  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. Description groups operations and provides context (e.g., 'parse relative expression like next monday'), adding moderate value beyond schema enum labels.

  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's for canonical date operations, lists specific operations (today, dow, validate, add/sub, parse, org-stamp), and emphasizes replacing date-from-memory usage. Distinguishes well from siblings (capture, search, ingest, status).

  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?

  Explicitly instructs 'ALWAYS use this instead of typing dates from memory' and explains why (LLMs hallucinate). While no explicit when-not-to-use, context is clear and no sibling alternatives exist.

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

• datacore_statusA
  3.8/5.0
  Behavior3/5

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

  No annotations provided, so description carries burden. 'Show' suggests read-only, but no explicit statement about side effects, permissions, or data freshness. 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?

  Single sentence with no filler, front-loaded with action and resource. Every word adds value.

  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 zero parameters and no output schema, description sufficiently covers purpose. Could mention if data is live or cached, but not required for basic status 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?

  No parameters exist and schema coverage is 100%. Baseline of 4 applies; description adds nothing about params but none needed.

  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 uses specific verb 'Show' and resource 'Datacore status', listing concrete aspects (note counts, module health, update info). Clearly differentiates from sibling tools like datacore_capture or datacore_search.

  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 or when to avoid. Does not mention alternatives or prerequisites. Implies usage for status checks but lacks detail.

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