Server Quality Checklist

Tool Scores

• query_buildC
  2.9/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden for behavioral disclosure. It never states whether the tool executes the generated query or only produces SQL text, whether a database connection is required, or what an empty/malformed description yields. This ambiguity is meaningful for a query tool, especially in the absence of any safety annotations.

  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 two sentences with the purpose up front and a useful, concrete example. No wasted words. It loses one point only because it forgoes any sibling differentiation or usage note that the space could afford.

  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 3-param generation tool with full schema coverage, the description conveys the core function adequately. However, it omits the execution-vs-generation distinction and the output shape (what exactly the tool returns), which is not covered by an output schema. This is a moderate gap for an un-annotated 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%, so all three parameters are already documented in the schema. The description's example only illustrates the 'description' parameter and adds no additional semantics for dialect or schema_hint beyond what the schema provides. Baseline 3 applies since the schema does the heavy lifting.

  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 states a clear, specific operation: build SQL from natural language descriptions, and the example makes the behavior concrete. It is implicitly distinguishable from siblings (sql_format, sql_explain, schema_analyze, migration_generate all operate on existing SQL/schema, not generate from prose), but it does not explicitly name or contrast those alternatives, so it stops short of a 5.

  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?

  There is no guidance on when to use this tool versus any sibling. It does not state use cases, exclusions, or mention that sql_format/sql_explain are better suited for handling existing SQL text. The reader must infer the intended usage from the purpose alone.

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

• migration_generateA
  3.6/5.0
  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 of behavioral disclosure. It states that both up and down migrations are generated, which is a useful behavioral detail. However, it does not disclose whether the tool is read-only, what happens for invalid or identical schemas, or any side effects. It also doesn't mention the return format (string vs object with up/down keys). This is a moderate gap given 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.

  Conciseness4/5

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

  The description is a single, efficient sentence that front-loads the primary action (compare) and specifies the output (ALTER TABLE migrations with up and down). No waste or filler. It could be slightly more structured (e.g., bullet points for inputs/outputs), but it's appropriately compact and readable.

  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 3 parameters, no output schema, and no annotations, the description is adequate but incomplete. It mentions the output nature (ALTER TABLE statements with up/down) but doesn't specify the exact return format (e.g., a single string, a JSON object with up/down fields, or a list). It also doesn't say whether multiple CREATE TABLE statements are supported in one input string. These are important details for an agent to correctly consume the result. Given the tool's moderate complexity, there is room for improvement.

  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?

  Input schema has 100% coverage, with clear descriptions for old_schema, new_schema, and dialect (enum). The description adds minimal extra meaning beyond the schema: it clarifies that schemas are CREATE TABLE statements and that migrations include both directions, but it doesn't explain the dialect enumeration or expected string formatting beyond the schema. Baseline 3 is appropriate since the schema carries the parameter definitions.

  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: compare two schemas (old vs new CREATE TABLE statements) and generate ALTER TABLE migration statements with up and down versions. It names the specific resource (schemas), action (compare and generate), and output (migration statements). This distinguishes it from siblings like sql_format (formatting), query_build (building queries), sql_explain (explain plans), and schema_analyze (analysis).

  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 use case: when you have an old and new schema and want to generate migration SQL. It does not explicitly warn against using this tool for other tasks or mention alternatives. Sibling tools like schema_analyze might be preferred for analysis, but the description doesn't address any exclusions or routing. The guidance is implicit rather than explicit.

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

• sql_explainA
  3.6/5.0
  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 implies a read-only analysis operation (explaining does not suggest mutation), and mentions outputs like tables, columns, conditions, and optimization tips. However, it does not explicitly state that the query is not executed, nor describe potential error behavior or output format details. This is adequate for a simple analysis tool but lacks explicit safety confirmation.

  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, front-loaded with the primary action ('explain'), followed by a list of sub-features. Every word adds value, with no filler or 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?

  For a tool with one parameter and no output schema, the description is largely complete: it tells the agent what to provide (a SQL query) and what to expect (plain English explanation with structural analysis and optimization tips). Minor gaps include not specifying whether the query needs to be valid or if it supports all SQL dialects, but these are not critical for basic 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?

  The input schema already describes the sole parameter as 'The SQL query to explain' with 100% coverage. The description adds no additional meaning about the parameter's format, syntax, or validation. Per the rubric, baseline 3 applies when schema coverage is high, and the description does not need to add more.

  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 'explain' applied to a SQL query, and specifies the output: step-by-step plain English, identification of tables, columns, conditions, and optimization tips. This distinguishes it from siblings like sql_format (formatting) and query_build (constructing queries).

  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 this tool vs the alternatives. It does not mention when not to use it, such as for formatting or building queries, nor any prerequisites like valid SQL syntax. The context must be inferred from the name and description.

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

• schema_analyzeA
  4.1/5.0
  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 parses SQL and generates a Mermaid ER diagram, implying a read-only analytical operation with no side effects. It does not discuss error handling or dialect support, but the core behavior is transparent.

  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 concise sentences, front-loaded with the primary action and explicit output. 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?

  The tool has a single parameter and no output schema. The description explains the main outputs (extracted schema elements and a Mermaid diagram), but it does not specify the exact response structure or whether both outputs are returned together. There is also no mention of error handling or edge cases, which is a gap for a tool that parses user-provided SQL.

  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 fully documents the 'sql' parameter with a description that already states it contains CREATE TABLE statements and can include multiple tables. The tool description adds context about what will be extracted but does not provide additional semantic details about the parameter itself (e.g., format constraints, limits).

  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 ('Parse') with a clear resource ('CREATE TABLE statements') and explicitly lists the extracted entities (tables, columns, types, constraints, foreign keys, indexes) and the generated output (Mermaid ER diagram). This clearly distinguishes it from siblings like sql_format or query_build, which serve 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 Guidelines4/5

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

  The description clearly states what the tool does, making it obvious when to use it (when schema analysis of CREATE TABLE statements is needed). However, it does not explicitly contrast it with sibling tools or state when not to use it, so it falls short of a perfect 5.

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

• sql_formatA
  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 behavioral burden. It discloses output-shaping behavior (indentation, uppercase keywords, column alignment) and supported SQL dialects, which is sufficient for a pure formatter. It does not explicitly state that the tool returns the formatted string without executing the query, but the verb 'format' strongly implies a transformation.

  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?

  A single sentence that front-loads the core action and follows with the relevant formatting details and supported dialects. No filler or 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?

  The description covers the tool's purpose, transformation behavior, and supported dialects, which is enough for a low-complexity formatter. The main gap is the absence of any explicit statement about the return value or that no SQL execution occurs, but given the tool's nature and the fully documented parameters, this is minor.

  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%, so the baseline applies. The description only loosely echoes parameter behaviors (indentation, uppercase, alignment) and adds no new detail about defaults, dialect handling, or edge cases beyond what the schema already documents.

  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 opens with a specific verb and resource: 'Format and prettify SQL queries,' and lists concrete transformations (indentation, uppercase keywords, aligned columns). This clearly differentiates it from siblings like query_build or sql_explain.

  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 intended use case is clear: when an agent needs to format/prettify SQL. It does not mention when not to use it or point to alternatives, so it stops short of explicit routing.

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