get_table_context

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, and destructiveHint=false, so the safety profile is covered. The description adds genuine behavioral value by clarifying the read is metadata-only and explicitly excludes business row data, which is the key operational distinction. It does not cover error behavior, cost, or latency.

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?

A single front-loaded sentence that first states the scope (connection → exact database/schema) and then the metadata categories, closed by a semicolon-delimited exclusion. No filler, no restatement of the tool name.

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?

With no output schema, the description usefully enumerates the returned metadata categories (columns, comments, keys, indexes, approximate row count) and explicitly scopes out row data, which is what an agent needs to decide whether to call it. Only finer return-shape details and pagination/limits are unspecified.

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?

Schema coverage is 75%, with the 'table' parameter lacking a description in the schema. The description compensates by clarifying that table accepts either a table OR a view ('表或视图'), and by emphasising that database/schema must be exact ('精确'), reinforcing the precision requirement on parameters that would otherwise be guessable.

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 names a specific verb (读取/read) and enumerates exactly what metadata is retrieved: columns, comments, primary/foreign keys, indexes, and approximate row count, scoped to a precise database/schema. The explicit '不读取业务行' (does not read business rows) cleanly separates it from siblings like execute_query or scan_database.

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?

It states the operating context (metadata inside a specific DBeaver connection/database/schema) and provides one explicit exclusion ('does not read business rows'), which implicitly routes data-reading tasks elsewhere. It stops short of naming the alternative tool or stating prerequisites like 'connection must already exist' and 'database/schema must be discovered first', which the schema fields carry instead.

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