Server Quality Checklist

Tool Scores

• list_databasesA
  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 burden of behavioral disclosure. It does state that the tool lists only files with .db, .sqlite, or .sqlite3 extensions, which signals a read-only discovery operation. However, it leaves ambiguity about whether the search is recursive, how hidden or unreadable files are handled, and what happens when no databases are found.

  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 with no filler, and the core action, resource, scope, and file extensions are all front-loaded. Every part of the sentence earns its place.

  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?

  This is a simple tool with one well-documented parameter and an output schema, so the basic invocation is fully specified. The description is missing a little context around recursive vs. top-level search and how it fits into the sibling tool workflow, but an agent can reasonably invoke it correctly.

  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 directory parameter is already fully documented, including its default value. The description reinforces the directory scope but adds no new semantic detail beyond what the schema provides, 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 ('List'), identifies the resource ('SQLite database files'), names the exact file extensions, and scopes the action to a directory. This clearly distinguishes it from sibling tools like schema, table_info, and query, which operate on databases rather than discover them.

  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 about when to use this tool versus the sibling tools, no stated workflow such as 'use before query', and no explanation of when another tool would be more appropriate. The intended usage as a discovery step is only implied by the tool name and siblings.

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

• queryA
  3.6/5.0
  Behavior3/5

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

  With no annotations, the description carries the full disclosure burden. It usefully mentions parameter binding, token-efficient formatting, and protections like opcode watchdog and cell truncation. However, it does not disclose whether writes can occur when readonly=false, nor does it describe side effects, failures, or error behavior.

  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?

  Three tight sentences, front-loaded with the verb and resource, followed by output-format variety and safety protections. No filler, no redundant restatement of the schema.

  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 rich input schema, output schema, and protective details in the description, an agent has enough to invoke the tool correctly. The main missing piece is guidance on when to choose this over sibling tools, which prevents a higher score.

  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 six parameters. The description's mention of parameter binding and output formats is consistent but adds little meaning beyond the parameter descriptions already present. Baseline 3 applies.

  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 opens with a specific verb and resource: 'Execute a SQL query against a SQLite database.' It also names output formats, making the tool's core function clear. It does not explicitly distinguish itself from siblings like explain or export_query, though the function is inferable.

  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 intended use is implied by 'Execute a SQL query,' but there is no explicit when-to-use guidance or mention of alternatives such as explain, export_query, or schema. An agent gets no direct help choosing among sibling tools.

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

• schemaA
  3.9/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the burden. It goes beyond the tool name by specifying the full result scope and making an explicit performance claim ('sub-millisecond O(1) row counts'). It doesn't discuss failure modes, but for a read-only introspection tool this is reasonably 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?

  One front-loaded sentence states the action and resource, followed by a compact list of contents. It is efficient and scannable, though splitting into two sentences would improve readability slightly.

  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 an output schema and a single well-documented optional parameter, nothing critical is missing. The description covers the result contents and performance. It doesn't explicitly distinguish from table_info, but that gap is more about usage guidance than 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 input schema covers 100% of the single parameter's semantics, including accepted file extensions and default-database behavior. The tool description itself adds no parameter detail, but that is acceptable given the high schema coverage baseline.

  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 names a specific verb and resource: 'Get the schema of a SQLite database,' and enumerates the concrete contents (tables, views, columns, data types, constraints, indexes, foreign keys, row counts). This clearly differentiates it from sibling tools like query, explain, and table_info.

  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 database-wide schema introspection by listing all tables and views, which hints at when to use it. However, it never explicitly contrasts this with table_info or says 'use table_info for a single table,' so alternatives are left to inference rather than stated.

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

• explainA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden of behavioral disclosure. It names the output as a query plan and the purpose as analysis, implying read-only behavior, but it does not explicitly state that the query is not executed or describe any output format/limitations.

  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, tightly worded sentence with no filler. It front-loads the core action and immediately explains the tool's practical 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?

  With an output schema present and complete parameter documentation, the description covers the essential context. A slight gap is the absence of an explicit note that this tool analyzes rather than executes the query, which would further differentiate it from the query sibling.

  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 three parameters (db, sql, params). The description adds no extra parameter-level detail, but this is acceptable given the strong schema 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 uses a specific verb and resource ('Explain the query plan for a SQL query') and explicitly names the underlying SQLite command (EXPLAIN QUERY PLAN). It clearly distinguishes itself from siblings like query, which executes queries, and schema/table_info, which inspect structure.

  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 communicates clear context for use: analyzing indexes and optimizing query performance. It does not explicitly name sibling alternatives or state when not to use the tool, but the stated purpose is sufficient to guide selection among the listed siblings.

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

• table_infoA
  4/5.0
  Behavior4/5

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

  With no annotations present, the description carries the full behavioral burden. It clearly frames the operation as a read-only 'Get' and adds meaningful detail: the row count is explicitly an estimation, and it discloses that the tool returns generated DDL and multiple metadata categories. It omits an explicit read-only or permission note, but the wording adequately signals a non-mutating 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 a single, well-structured sentence that front-loads the action and object, then uses a colon-delimited list to pack the full set of returned information. There is no filler or repetition.

  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 that an output schema exists and both parameters are fully documented in the input schema, the description covers purpose and the key behavioral nuance (estimated row count). It does not explicitly route to sibling tools, but an agent has everything needed to invoke the tool correctly.

  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 description coverage is 100%: both db and table already carry descriptive text in the schema. The tool description adds no parameter-specific meaning beyond what the schema states, so it stays at the baseline for high schema 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 uses a specific verb and resource: 'Get detailed info about a single table or view,' followed by a concrete enumeration of what is returned (columns, types, constraints, indexes, foreign keys, triggers, DDL SQL, row count estimation). The 'single table or view' qualifier and the depth of listed details distinguish it from sibling tools like schema and query.

  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 is given on when to use table_info versus the sibling tools (schema, query, explain). The description implies a use case through scope ('single table or view') and the detailed metadata list, but it does not state when to choose it over alternatives or mention any exclusions.

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

• export_queryA
  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 disclosure burden. It discloses key behaviors: streaming results directly to disk, zero token consumption, and constant memory usage. It stops short of stating file-overwrite behavior, but the core side effect and performance traits are 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?

  The description is a single efficient sentence that front-loads the core action and result, then adds the most distinctive benefits (zero token consumption, O(1) memory) without filler.

  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 a fully documented schema and an output schema, the description is largely complete: it explains what happens, where output goes, and why it is useful. It could more explicitly contrast with the query sibling or mention overwrite behavior, but those are minor omissions rather than blockers.

  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 parameters are already well-documented. The description reinforces the CSV/JSONL file destination and SQL execution, but adds little semantic value beyond what the schema provides.

  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 ('Execute') and resource ('SQL query') and clearly states the outcome: streaming results to a local CSV or JSONL file. This makes it easy to distinguish from sibling tools like query, which would return results in-context rather than writing to disk.

  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 gives clear context for when to use this tool: 'ideal for large query exports' and highlights zero token consumption and O(1) memory usage. It does not explicitly name alternatives or state when-not-to-use, but the use case is clear enough to guide selection.

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