Server Quality Checklist

Tool Scores

• design_system_architectureB
  3.4/5.0
  Behavior2/5

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

  No annotations are provided, so the description must fully disclose behavioral traits. It states the tool 'designs' but does not mention side effects (e.g., whether it creates any permanent state), authorization needs, rate limits, or response characteristics. The mention of 'GLM-4.6' is a technical note, not a 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?

  The description is a single sentence that front-loads the action ('Design a complete system architecture') and then enumerates outputs. It is efficient with no wasted words. However, it could be restructured to improve readability (e.g., list outputs separately).

  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 the tool's complexity (architecture design) and lack of output schema, the description is somewhat sufficient by listing expected outputs. However, it omits any indication of output format, depth, or constraints (e.g., size limits). With no annotations and no output schema, additional context would help agents understand what to expect.

  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% for the single parameter 'requirements', which is described as 'Detailed system requirements, constraints, and objectives'. The tool description adds minimal extra meaning beyond noting it is 'based on requirements'. Baseline 3 is appropriate as the schema already carries the parameter semantics.

  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 function: designing system architecture. It lists specific deliverables (component breakdown, data flow patterns, technology recommendations, deployment strategies), making the purpose concrete. While it doesn't explicitly differentiate from siblings, the verb 'design' and outputs distinguish it from analysis, consultation, or review tools.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies use when requirements are available ('based on requirements'), but it provides no explicit guidance on when to use this tool versus siblings, nor any exclusion criteria. Without context on prerequisites or alternatives, agents must infer appropriate usage.

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

• consult_architectureA
  3.7/5.0
  Behavior2/5

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

  No annotations provided, so description carries full burden. It lacks details about behavioral traits such as response format, limitations, or interaction style beyond generic 'guidance'. This leaves the agent unclear on what to expect.

  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 front-loaded with purpose and usage. Every sentence adds value with no redundancy.

  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 simple consultation tool with no output schema or annotations, the description covers purpose and usage but omits behavioral details and return format. Adequate but not complete.

  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 for both parameters. The tool description does not add any additional meaning beyond the schema, so 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 specifies 'Consult GLM-4.6 for expert software architecture guidance...' with clear verb and resource, and distinguishes from siblings by focusing on high-level architectural questions requiring deep expertise.

  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 states when to use: 'Use this for high-level architectural questions requiring deep technical expertise.' However, it does not mention when not to use or directly contrast with sibling tools.

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

• review_technical_decisionA
  3.7/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It describes the tool's function (assessing impact, etc.) but does not disclose whether it is read-only, has side effects, or any limitations. It is adequate but could be improved with more behavioral context.

  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 no wasted words. The first sentence states the core purpose, the second expands on the evaluation scope. Excellent front-loading and efficiency.

  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?

  The description covers the main purpose and evaluation areas but does not specify the return format or any error cases. With no output schema, some description of the output structure would improve completeness. Adequate for a simple tool.

  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% with clear parameter descriptions. The tool description adds context about the expertise used but does not provide substantial additional meaning beyond the schema. 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 verb 'Review and evaluate' and the resource 'technical decision'. It adds specificity by mentioning 'using GLM-4.6 architectural expertise' and lists what will be assessed (impact, trade-offs, alternatives, risks) and output (recommendations). This distinguishes it from sibling tools like 'consult_architecture' which are more general.

  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?

  No explicit guidance on when to use this tool versus alternatives like 'analyze_code_architecture' or 'design_system_architecture'. The description implies usage for structured decision review but does not state when not to use it or provide context for selection.

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

• analyze_code_architectureA
  3.8/5.0
  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 the tool uses GLM-4.6 and evaluates specific aspects, but does not explicitly state whether it is read-only, what permissions are needed, or any potential side effects. The description is adequate but lacks depth.

  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, well-structured sentence that efficiently communicates purpose and scope without unnecessary words. Every part 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?

  For a tool with three required parameters and no output schema or annotations, the description covers the key aspects of what is analyzed. However, it lacks information about the output format or structure, which would enhance completeness. Overall, it is nearly complete.

  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% (all parameters have descriptions in schema). The description does not add additional meaning beyond the schema—it focuses on overall analysis scope rather than parameter-specific details. Baseline score of 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 it analyzes code from an architectural perspective using a specific model (GLM-4.6) and lists evaluation areas (design patterns, SOLID, scalability, security, improvements). This distinguishes it from siblings like 'consult_architecture' or 'design_system_architecture'.

  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 the tool is for architectural analysis of code but provides no explicit guidance on when to use it versus siblings, nor does it mention prerequisites or exclusions. Usage is inferred but not clarified.

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

• advanced_reasoningA
  4.2/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden. It discloses that the tool consults GLM-4.6, delivers rigorous methodology, and outputs XML structure optimized for Claude 4.5 Sonnet. This goes beyond basic purpose and gives useful behavioral insight.

  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 extremely concise, consisting of two sentences that front-load the core purpose and key use cases. Every phrase adds value with no redundancy.

  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 three required parameters and no output schema, the description covers the tool's purpose, use cases, and even hints at the output format. It is mostly complete but could elaborate on limitations or error handling.

  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 input schema has 100% parameter description coverage, so the schema already documents each parameter adequately. The description does not add new parameter-level detail beyond the schema, meeting the baseline expectation.

  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 identifies the tool for advanced mathematical, algorithmic, and scientific reasoning tasks. It lists specific use cases such as complex algorithms, mathematical proofs, and performance optimization. This effectively differentiates it from sibling tools focused on architecture and code analysis.

  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 lists when to use the tool by enumerating domains and tasks. However, it does not provide explicit guidance on when not to use it or mention alternative tools, though the sibling context implies boundaries.

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