列出达梦中的表

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

Annotations already mark the tool read-only and idempotent. The description adds useful behavior beyond annotations: NUM_ROWS is from statistics and may be NULL, and identifiers are case-insensitive. No contradictions with the annotations.

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?

Three compact sentences each earn their place: what the tool returns, when to use it and the count caveat, and the case-insensitivity note. Information is front-loaded and no filler is present.

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?

For a read-only list tool with no required params and no output schema, the description covers the return shape (row count, tablespace, comment), the main data-quality caveat, and the alternative for exact counts. Remaining defaults and format are already documented in the schema.

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 100%, so baseline is 3. The description adds context beyond schema by illustrating pattern matching ('ORDER matches data_order_main') and confirming case-insensitive identifiers, which helps the agent use owner/pattern correctly.

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?

Description states a specific action (list tables in DM8 by schema/name keyword) and the exact payload (row-count statistics, tablespace, comments). It clearly positions the tool as an exploration helper, which differentiates it from sibling tools like dm_describe_table or dm_table_count.

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?

Gives explicit usage scenarios ('which tables are in this library', 'find order-related tables') and an explicit alternative: use dm_table_count when accurate row counts are required. This satisfies the when/when-not/alternatives criterion.

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