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execute_query

Execute read-only SELECT queries to retrieve data, count rows, aggregate, and join tables. Write operations are blocked for security.

Instructions

Execute read-only SELECT queries. Writes are blocked.

LEVEL: Data (actual table data retrieval)

USE FOR: fetching data, counting rows, aggregations, joins. DO NOT USE FOR: INSERT/UPDATE/DELETE (use analyze_impact first).

ERROR RECOVERY:

  • "relation does not exist": Verify table name with get_schema()

  • "permission denied": User lacks SELECT privilege on table

  • "query timeout": Reduce limit, add WHERE clause, or increase timeout_ms

  • "not connected": Call connect() first

Examples: execute_query(query='SELECT * FROM users LIMIT 10') execute_query(query='SELECT COUNT(*) FROM orders')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSQL SELECT query
limitNoMax rows (1-50000)
timeout_msNoTimeout in ms (5 min default)
formatNoOutput formatjson
urlNoDatabase URL

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Despite no annotations, the description fully discloses read-only behavior, write blocking, and connection requirements. Error recovery provides behavioral insights for common failure modes, adding depth beyond structured metadata.

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 well-structured with a bold intro, use/do-not-use sections, error recovery bullets, and examples. It is front-loaded with core purpose, and each section is concise and relevant, earning its place.

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?

Given the tool's complexity (5 params, 1 required, no annotations) and the presence of an output schema, the description covers purpose, usage boundaries, error recovery, and examples comprehensively. It leaves no significant gaps for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds substantial value with usage examples, error handling for timeouts and limits, and contextual guidance on parameters like format and limit. This goes well beyond the schema 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 'Execute read-only SELECT queries' with the verb 'execute' and resource 'SELECT queries'. It distinguishes from write operations and provides the data retrieval level, making its 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?

Explicitly lists use cases (fetching data, aggregations) and forbids INSERT/UPDATE/DELETE, directing users to analyze_impact. Includes error recovery steps with specific error messages and actions, offering comprehensive guidance.

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

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