Server Quality Checklist

Tool Scores

• list_tablesA
  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 of behavioral disclosure. It states 'Read-only,' mentions audit logging ('Every call is written to the audit ledger'), and explains that 'tables the policy denies are absent rather than marked.' These are valuable side-effect and security behaviors beyond basic operation.

  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 concise (three sentences) and front-loaded with the core purpose. Each sentence adds value: purpose, usage guidance, return format, and behavioral notes. No fluff or redundancy, making it highly efficient.

  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 there is no output schema, the description explicitly explains the return format ('one entry per table with its connector, schema-qualified name and description') and the denial behavior. It covers usage and side effects adequately for a simple list operation, though it omits error handling or pagination details, which slightly reduces 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 single parameter 'connector' is fully described in the schema (100% coverage) as 'Connector name (optional, defaults to all).' The description adds no additional parameter meaning; it only mentions connector as part of the output structure. Since schema coverage is high, 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 tool's purpose: 'List the database tables this gateway is allowed to expose.' It uses a specific verb (list) and resource (database tables), and explicitly distinguishes itself from siblings like describe_table and query by noting it provides the authoritative list of reachable tables. This is a model of purpose clarity.

  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 provides explicit guidance: 'Call it before describe_table or query when the table names are not already known.' This tells the agent when to use it (before others when names unknown), but does not explicitly state when not to use it or mention alternative tools. It implies usage context but falls short of full when/when-not coverage.

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

• queryA
  4.5/5.0
  Behavior5/5

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

  With no annotations, the description carries the full burden. It discloses multiple behavioral traits: only SELECT allowed, row caps, masking of sensitive values, refusal as normal outcome, audit logging, and optional signed receipts. It also warns that raw protected values never reach the caller, which is critical for planning. This is exceptionally transparent.

  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 moderately long but every sentence adds value: purpose, restriction, behavior, alternative, and audit trail. It is front-loaded and well-organized. Slightly verbose but not wasteful, so a 4 is warranted.

  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, constraints, safety features, and alternatives. Without an output schema, it doesn't specify the exact return format (e.g., column details or metadata), but it does clearly state rows come back capped and masked. Given the complexity (SQL execution with policies), it is fairly complete, though a bit more detail on response structure would be useful.

  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% — both parameters have clear descriptions in the schema. The tool description adds minimal parameter-specific detail beyond what schema provides, but it does mention the connector defaults to first allowed, which is already in the schema. Given high coverage, the baseline 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 the tool runs a read-only SELECT query on the database, explicitly limits to SELECT, and distinguishes from sibling tools like search (used when there is no SELECT yet). It names the resource (company database) and the verb (run), making the purpose 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 explicitly says when to use this tool vs alternatives: 'Use search instead when there is no SELECT yet and the goal is to find text.' It also clarifies that refusals are normal, setting expectations for failed invocations. This is explicit and actionable guidance.

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

• describe_tableA
  4.7/5.0
  Behavior5/5

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

  Despite no annotations, the description thoroughly discloses behavior: read-only, no row reads, no masking, error on denied tables, and audit logging. This fully compensates for lacking annotations.

  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?

  Four concise sentences with high information density. Every sentence adds value: purpose, read-only assurance, usage tip, error behavior, and audit logging.

  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?

  Complete for a read-only metadata tool. Covers purpose, usage order, error cases, audit trails, and privacy implications despite no annotations or 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 coverage is 100%, so parameters are documented in the schema. The description mentions 'a table' and 'if the table name is not known', but adds no extra parameter-specific detail beyond the schema.

  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 describes columns of one table with name, type, and description. It differentiates from siblings like search, list_tables, and query by specifying its specific role in understanding table structure.

  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?

  It explicitly says 'Use it to write a correct query' and 'use list_tables first if the table name is not known', providing clear guidance on when to use this tool vs. alternatives.

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

• searchA
  4.9/5.0
  Behavior5/5

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

  Despite the absence of annotations, the description discloses critical behaviors: read-only nature, result capping by maxRows, masking of PII/secrets, audit logging, and optional signed receipts. It also clarifies that the policy determines searchable scopes, giving the agent a solid mental model of side effects and constraints.

  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 compact and information-dense, with no fluff. It front-loads the core purpose, then gives usage guidance, return behavior, and audit details in four sentences, each earning its place. Perfectly sized for quick scanning.

  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?

  For a tool with 3 parameters and no output schema, this description covers all necessary context: what it does, how it relates to the query sibling, what the returned data looks like (masked, capped), and the auditing side effect. There are no obvious gaps that would leave an agent confused about when or how to invoke it.

  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?

  Schema coverage is 100%, so the baseline is 3. The description adds useful context by explaining that the search runs across 'allowed tables' and that results adhere to the same policy as 'query', which enriches understanding of the 'tables' and 'query' parameters. It doesn't go into per-parameter syntax, but it doesn't need to; the brief schema descriptions are sufficient.

  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 begins with a specific verb+resource: 'Find rows by a search term across the allowed tables — no SQL required. Read-only.' It clearly distinguishes the search use case from the sibling 'query' tool, stating when to use which.

  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?

  Explicit when-to-use guidance is provided: 'Use it when the goal is to look up text and there is no SELECT yet; use query when a SELECT already exists.' This directly names the alternative and sets a clear decision rule, which fully addresses when to use this tool vs. the main sibling.

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