Retrieve a Power BI table's columns, data types, and measures to understand its structure before writing DAX queries.
Mô tả 1 bảng: danh sách cột (tên + kiểu dữ liệu) và các measure đặt trong bảng đó.
port / model_id: lấy từ list_local_reports.
table_name: tên bảng (lấy từ list_tables).
| Name | Required | Description | Default |
|---|---|---|---|
| port | Yes | ||
| model_id | Yes | ||
| table_name | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.7.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. 'Mô tả' (describe) implies a read-only operation and the description usefully discloses what is returned (columns and measures), but it does not affirm non-mutation, permissions, or error behavior. Output schema exists, so return-format details are reasonably omitted.
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 short front-loaded lines with zero waste: purpose first, then per-parameter sourcing. Every sentence earns its place.
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 describe tool with an output schema present, the definition covers purpose, return contents, and all three parameter sources. Nothing critical is missing, though a note on whether measures are included conditionally or scope limits would round it out.
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 description coverage is 0%, so the description must compensate — and it does, explaining the meaning and provenance of all three required parameters (port/model_id from list_local_reports, table_name from list_tables). This is meaningful added value over bare string titles in the schema.
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?
States a specific verb (describe) and resource (table), and names the exact return content: column names + data types plus measures defined on the table. This distinguishes it from list_tables (enumerate) and list_local_reports, though it doesn't explicitly contrast itself with them.
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 clear prerequisite chaining by stating port/model_id come from list_local_reports and table_name from list_tables, which implicitly defines the workflow ordering. It does not explicitly state when NOT to use it, but the context is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.