Server Quality Checklist

Tool Scores

• analyze_database_schemaB
  3.2/5.0
  Behavior2/5

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

  No annotations are provided, so the description must carry the full burden of behavioral disclosure. It says 'Analyze' which implies a read-only operation, but doesn't explicitly state that it won't modify anything, nor does it mention potential performance impacts of sampling data or usage on production environments. This lack of detail is a significant gap for a tool with zero annotation coverage.

  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 of about 15 words, front-loaded with the verb and resource. Every word is informative, with no redundancy or filler. It is well-structured and immediately conveys the tool's 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?

  There is no output schema, so the description should explain what the analysis returns (e.g., a report, schema representation, or diagnostics). It does not. Given the tool has 3 parameters and covers multiple aspects of the schema, the description is incomplete. It also fails to mention any caveats like environment differences or performance considerations.

  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 baseline is 3. The description mentions 'optional sample data', which aligns with includeSamples and maxSampleRows, but adds no additional semantic detail beyond what the input schema already provides. It neither clarifies parameter formats nor explains edge cases.

  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 'Analyze' and the resource 'D1 database schema', listing specific aspects (tables, columns, indexes, relationships) and optional sample data. It distinguishes this from sibling tools like get_table_relationships by its broader scope, though it doesn't explicitly contrast with them.

  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 usage for general schema analysis, but provides no explicit guidance on when to use this tool versus siblings like validate_database_schema or suggest_schema_optimizations. There are no exclusions or alternative recommendations, so using it is inferred rather than directed.

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

• get_table_relationshipsB
  3.2/5.0
  Behavior2/5

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

  With no annotations available, the description carries the full burden of disclosure. It does not state whether the operation is read-only, what side effects might occur, what output format to expect, or any other behavioral traits. The vague 'analyze' adds little 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?

  The description is a single, clear sentence that is front-loaded with the tool's purpose. No unnecessary words or repetition, making it appropriately concise.

  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?

  Despite having a simple schema, the tool has no output schema, so the description should explain what the return value looks like and what 'analyze' entails. It does not, leaving the agent without critical context for interpreting results or understanding the tool's full behavior.

  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 both parameters already explained (tableName filter and environment). The description adds no additional meaning to the parameters, so the baseline of 3 applies.

  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 with a specific verb ('Extract and analyze') and resource ('foreign key relationships between tables'), and it distinguishes itself from sibling tools that focus on broader schema analysis, validation, optimization, or comparison.

  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, no exclusions or prerequisites are mentioned. The description implies usage through its purpose but offers no explicit context or 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.

• validate_database_schemaB
  3.2/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It states what the tool detects but does not mention whether it is read-only, whether it modifies data, what the output format is, or if it requires special permissions. This is a meaningful gap for a validation tool that could potentially be expected to run side-effect-free checks.

  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 front-loads the primary action ('Validate database schema integrity') and then provides concrete examples to clarify scope. There is no redundant wording or filler, and every part of the sentence contributes useful information.

  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?

  The tool has no output schema and no annotations, yet the description does not explain what the result looks like or how issues are reported. Given the presence of sibling tools with overlapping purposes, the description also fails to clarify the tool's unique position. While the single parameter is well-documented, the lack of return-value or behavioral context leaves the description incomplete.

  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% schema description coverage: the single parameter 'environment' is fully described with an enum of valid values and a clear meaning. The description adds no additional semantic detail beyond the schema, so the 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 uses a specific verb ('Validate') with a clear resource ('database schema') and enumerates concrete examples of what it checks (missing primary keys, orphaned foreign keys). This distinguishes it from related sibling tools like analyze_database_schema and suggest_schema_optimizations, which imply broader or different scopes.

  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?

  The description provides no explicit guidance on when to use this tool versus alternatives such as analyze_database_schema or compare_schemas. It does not mention any exclusions, prerequisites, or scenarios where another tool would be preferred, leaving the agent to infer usage solely from the tool name and purpose.

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

• suggest_schema_optimizationsB
  3.3/5.0
  Behavior2/5

  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 implies a read-only analysis ('analyze and suggest'), but does not explicitly state that it makes no changes, nor does it describe the output format or any permissions/limitations. This leaves significant behavioral ambiguity.

  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, focused sentence with parenthetical examples. It is front-loaded with the core action and contains no wasted words.

  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 tool with one enum parameter, the description plus schema provides a basic understanding. However, the lack of usage guidance, explicit read-only nature, and output expectations leaves gaps that a more complete description would fill. The 'etc.' hints at additional optimizations but does not elaborate.

  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% description coverage: the sole parameter 'environment' is well-described with an enum list, so the schema already conveys complete parameter semantics. The description does not add further parameter detail, but none is needed.

  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 a specific action ('Analyze schema and suggest performance optimizations') with concrete examples ('missing indexes, redundant indexes'). It is distinguishable from siblings like validate_database_schema or compare_schemas, though it could more explicitly contrast with analyze_database_schema, which may also analyze schema.

  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?

  Usage context is implied: the tool is for suggesting performance optimizations, not for general schema analysis or validation. However, there is no explicit guidance on when to choose this over analyze_database_schema or other siblings, nor any exclusions.

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

• compare_schemasA
  4/5.0
  Behavior3/5

  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 outputs ICE-scored differences and is used for migration planning, but it does not state whether the operation is read-only, any side effects, permissions needed, or what ICE-scored means. This adds some context beyond the name but leaves notable gaps.

  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 action, resource, and purpose without fluff. Every word contributes value, making it highly concise and well-structured.

  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 4 required parameters, no output schema, and no annotations, the description provides a clear purpose and mentions the ICE-scored output. However, it leaves some gaps: 'ICE-scored' is unexplained, and the phrase 'between environments' could be more precise given that the actual parameters are database IDs. Overall, it is fairly complete but not exhaustive.

  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 descriptions cover all 4 parameters (100% coverage), so the baseline is 3. The description adds no parameter-specific details beyond the general 'between environments' concept, which is already reflected in the schema's environment enums.

  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 (Compare), the resource (database schemas), and the scope (between environments), while also specifying the purpose (detect drift, plan migrations) and the distinctive output (ICE-scored differences). This effectively differentiates it from sibling tools like analyze_database_schema or validate_database_schema.

  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 the tool (comparing schemas across environments for drift detection or migration planning) and provides clear context. However, it does not explicitly mention when not to use it or name alternatives, which would elevate it to a 5.

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