read_data

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 adds value by specifying security constraints (must start with SELECT, no destructive operations) and the database type (MSSQL), which aren't in the schema. However, it lacks details on error handling, performance limits, or return format, leaving gaps for a tool that executes arbitrary SQL queries.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

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

The description is concise and front-loaded, with two sentences that clearly state the purpose and key constraints. There's no unnecessary repetition or fluff, and it efficiently communicates essential information without wasting words, though it could be slightly more structured for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of executing arbitrary SQL queries, no annotations, and no output schema, the description is moderately complete. It covers the core purpose and security constraints but lacks details on behavioral aspects like error messages, result formatting, or rate limits, which are important for an AI agent to use this tool effectively in context with its siblings.

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

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

The input schema has 100% description coverage, with the 'query' parameter well-documented in the schema itself. The description adds minimal semantic value beyond the schema by repeating the constraints (must start with SELECT, no destructive operations) but doesn't provide additional context like query formatting tips or examples not in the schema. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Executes a SELECT query on an MSSQL Database table.' It specifies the verb ('executes'), resource ('MSSQL Database table'), and operation type ('SELECT query'). However, it doesn't explicitly differentiate from sibling tools like 'list_table' or 'describe_table', which might also read data, so it falls short of a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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

The description provides some usage context by stating that the query 'must start with SELECT and cannot contain any destructive SQL operations for security reasons,' which implies this tool is for safe read-only queries. However, it doesn't explicitly mention when to use this tool versus alternatives like 'list_table' or 'describe_table' from the sibling list, leaving usage guidance incomplete.

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