Server Quality Checklist

Tool Scores

• tacit_graphqlA
  4.1/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, and idempotentHint=true, covering safety and idempotency. The description adds valuable context about the API's Brick-compliant schema, query capabilities, and auto-injection of siteId into variables, which helps the agent understand the tool's behavior beyond annotations.

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

  Conciseness2/5

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

  The description is overly long and includes extensive schema documentation (e.g., root queries, types, enums, examples) that belongs in external documentation. While informative, it's not front-loaded and contains redundant details that could be streamlined for an agent-focused tool description.

  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 complexity (GraphQL API with rich querying) and lack of output schema, the description provides comprehensive context including schema overview, filter guides, and examples. However, the excessive detail reduces focus on core agent guidance, though it compensates for missing output schema.

  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 the schema already documents all parameters (site_id, query, variables). The description adds minimal extra semantics (e.g., 'siteId is auto-injected'), but most parameter details are covered by the schema, meeting 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 explicitly states the tool's purpose as 'Execute a GraphQL query against the Tacit building digital twin API' with specific capabilities like nested fields, filtering, and supply chain traversal. It clearly distinguishes from sibling tools like tacit_list_sites (which provides site IDs) and tacit_timeseries (which likely handles time-series data).

  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?

  The description provides explicit guidance: 'Use tacit_list_sites first to get a valid site ID, then construct queries freely.' It clearly indicates a prerequisite (site ID from sibling tool) and when to use this tool (for GraphQL queries) versus alternatives (tacit_list_sites for IDs).

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

• tacit_list_filesA
  4.5/5.0
  Behavior4/5

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

  Annotations already cover key behavioral traits (read-only, open-world, idempotent, non-destructive), so the bar is lower. The description adds valuable context by specifying what types of files are returned (e.g., BIM source files, 3D models) and the filtering capabilities, which helps the agent understand the tool's behavior beyond the annotations. No contradictions with annotations exist.

  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 well-structured and front-loaded, starting with the core purpose, followed by return details, usage examples, and parameter/return summaries. Every sentence adds value without redundancy, and it efficiently covers necessary information in a compact format.

  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 moderate complexity (list operation with filtering), rich annotations (covering safety and behavior), and 100% schema coverage, the description is complete enough. It explains the purpose, usage context, and return values (though no output schema exists), providing sufficient information for an agent to use the tool effectively without overloading with redundant details.

  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 the schema already fully documents all parameters. The description adds minimal value beyond the schema—it mentions filtering by category and entity_uri but doesn't provide additional semantic context. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't significantly enhance parameter understanding.

  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 purpose with specific verbs ('List documents and files') and resources ('associated with a site'), distinguishing it from siblings like tacit_list_sites (which lists sites) and tacit_graphql (which performs GraphQL queries). It explicitly mentions the types of files returned (spec sheets, maintenance documents, etc.), making the scope unambiguous.

  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?

  The description provides explicit usage guidance with examples of when to use it ('Useful for answering questions like...'), mentions a prerequisite (site_id 'from tacit_list_sites'), and implicitly distinguishes it from siblings by focusing on file listing rather than site listing, GraphQL queries, or timeseries data. This gives clear context for when this tool is appropriate.

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

• tacit_list_sitesA
  4.7/5.0
  Behavior4/5

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

  Annotations already cover read-only, open-world, idempotent, and non-destructive traits, so the bar is lower. The description adds valuable context by explaining that sites are 'top-level containers' needed for querying other data (buildings, equipment, etc.), which aids in understanding dependencies and workflow, though it doesn't detail rate limits or auth specifics beyond API key access.

  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 front-loaded with the core purpose, followed by explanatory context and usage guidance in four concise sentences. Each sentence adds value: defining sites, their role, return format, and when to use the tool, 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 the tool's simplicity (0 parameters, no output schema) and rich annotations, the description is complete. It explains what the tool does, its importance in the workflow, and the return format, providing all necessary context for an agent to use it effectively without over-explaining.

  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 parameters and 100% schema description coverage, the baseline is high. The description adds no parameter-specific information (as there are none), but it clarifies the tool's scope ('all building sites the current API key has access to'), which implicitly defines the input context, earning a score above the minimum.

  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 action ('List all building sites') and resource ('sites'), distinguishing it from siblings like tacit_list_files (files) and tacit_timeseries (timeseries data). It specifies that sites are 'top-level containers' for physical locations, making the purpose specific and well-defined.

  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?

  The description explicitly provides usage guidance: 'Use this tool first to discover available sites before querying building data.' This indicates when to use it (as an initial discovery step) and implies alternatives (other tools for building data), offering clear context for selection.

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

• tacit_timeseriesA
  4.7/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds valuable context beyond this: it explains that points are identified by UUIDs, mentions the max limit of 200 point IDs, provides common usage patterns with examples, and describes the return format. While it doesn't detail rate limits or auth needs, it enriches the behavioral understanding significantly.

  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 well-structured and front-loaded with the core purpose. It efficiently uses bullet points for parameters and common patterns, avoiding redundancy. Every sentence adds value, such as clarifying sibling tool relationships and providing usage examples, 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 the tool's complexity (7 parameters, 2 required) and rich annotations, the description is highly complete. It covers purpose, usage guidelines, parameter details, behavioral context, and return values. Although there's no output schema, the description specifies the return format ('Array of series, each with timeseriesId, name, type, unit, equipment, and data records [{t, v}]'), filling that gap effectively.

  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 100% schema description coverage, the baseline is 3. The description adds meaningful semantics: it clarifies that point_ids are 'comma-separated timeseriesId UUIDs (max 200)', provides default values for optional parameters (e.g., start: '-1h', end: 'now()', aggregate: 'mean'), and gives practical examples like 'Last hour raw: start="-1h" (default)'. This enhances understanding beyond the schema's basic 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's purpose: 'Query historical or live sensor data for one or more points.' It specifies the resource (sensor data/points), the action (query), and distinguishes it from sibling tools by mentioning that point IDs come from 'tacit_graphql' and that for current/live values, 'tacit_graphql' should be used instead. This provides specific verb+resource differentiation.

  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?

  The description provides explicit guidance on when to use this tool versus alternatives. It states: 'Use tacit_graphql first to find points and their timeseriesId values' and 'For current/live values, use tacit_graphql with the currentValue { value timestamp quality } field on Point instead of this tool.' This clearly defines prerequisites and exclusions, helping the agent choose correctly.

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