Mostly Right

Archive a table

archive_table

Destructive

Retires one table from its dataset: it leaves the dataset's table list and frees its name for a new table. The versions it built are not deleted. The service confirms the archive with the table's current stored name itself, so you never send one. Example: {"table_id": "…"}. A live table is refused — call demote_table first. A table with a run still queued, held or running is refused too: cancel_run that run or wait for it to finish. Only call it when the person you are working for has asked for it. Returns {table_id, dataset_id, name, status, dashboard_url}.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "table_id": "<table_id>"
    },
    "name": "archive_table"
  }
}

Input Schema

Name	Required	Description	Default
`table_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 16, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond destructiveHint=true and idempotentHint=false, the description discloses what is and isn't destroyed (versions are kept, name is freed), the refusal conditions, and that the service supplies the stored name so the caller never sends one. This is unusually rich behavioral context for a destructive tool.

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

Conciseness4/5

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

Front-loads the effect, then the retention fact, then the input convention, refusals, consent, and return shape. Dense and information-rich, though the example payload and return-field list are slightly verbose for a one-parameter tool.

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?

No output schema exists, yet the description enumerates the return fields ({table_id, dataset_id, name, status, dashboard_url}), covers prerequisites, refusals, and safety behavior. Nothing an agent needs to invoke it correctly is missing.

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

Parameters4/5

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

Schema coverage is 0% for the single table_id param, so the description must carry meaning — and it does: it clarifies that table_id is the only input and that the name is resolved server-side, and it gives an example payload. It stops short of describing the uuid format, which the schema already pins down via pattern/format.

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?

States a specific verb and resource ('Retires one table from its dataset') and precisely describes the effect: it leaves the table list and frees the name, while versions are retained. This clearly separates it from sibling mutation tools like demote_table.

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?

Gives explicit exclusions and the alternatives for each: a live table is refused, call demote_table first; a table with a queued/held/running run is refused, cancel_run or wait. It also adds an explicit consent prerequisite ('Only call it when the person you are working for has asked for it').

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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