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cancel_progressive_analysis

Cancel a queued or running progressive analysis by request ID and mark its result stale, preventing outdated analysis from being used.

Instructions

Cancel queued or running progressive analysis and mark its result stale.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorYes
statusYes
context_idYes
request_idYes
analysis_idYes
schema_versionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

There are no annotations, so the description carries the full behavioral burden. It does disclose the core effect: queued or running analyses are cancelled and the result becomes stale. However, it omits permissions/ownership requirements, reversibility, idempotency, and error behavior.

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

Conciseness5/5

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

A single, front-loaded sentence that states the action and effect with zero wasted words. It is appropriately sized for a one-parameter cancellation tool.

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

Completeness3/5

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

An output schema exists, so return values need not be described. The description covers the core mutation and its visible effect, but for a tool with no annotations it is still missing prerequisites such as how to obtain request_id, permission requirements, and interaction with sibling tools.

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

Parameters2/5

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

Schema description coverage is 0%, and the single required parameter request_id is not explained in the description at all. The description does not say where the request_id comes from or how it relates to start_progressive_analysis or get_progressive_analysis, so it fails to compensate for the empty schema.

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

Purpose4/5

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

The description gives a specific verb ('Cancel'), a precise resource ('progressive analysis'), and scope ('queued or running'), plus the side effect of marking the result stale. It distinguishes itself from the generic cancel_analysis_job via the resource name, but it does not explicitly say how it differs from that sibling.

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

Usage Guidelines3/5

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

The eligible states ('queued or running') imply when cancellation is applicable, but the description never states when to choose this over cancel_analysis_job, nor what to do if the request has already completed. No alternatives are named.

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