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Stop a live dataset

caliper_source_feeds_stop
Destructive

Stops a source from adding new conversations to a dataset. What it already added stays. Get the feedId from caliper_source_feeds_list. May return needs_confirmation.

Input Schema

NameRequiredDescriptionDefault
feedIdYesLive dataset id, from caliper_source_feeds_list.
sourceIdYesSource id, from caliper_sources_list or search_workspace.
workspaceNoWorkspace slug. Personal tokens with no default workspace MUST pass this; tokens with a default can override per call. Ignored for workspace API keys.
approvalIdNoApproval id from a prior needs_confirmation response. Omit on the first call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and readOnlyHint=false, but the description adds genuinely useful non-obvious context: that stopping is non-retroactive ('What it already added stays') and that a `needs_confirmation` response is possible. It does not describe reversibility or how to restart ingestion, so it falls short of a 5.

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?

Three short sentences, front-loaded with the core action and its scope caveat, then the prerequisite and the possible response state. No filler and nothing redundant.

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

Completeness4/5

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

No output schema exists, so the description carries the return-value burden and does mention the possible `needs_confirmation` state. Combined with 100% schema coverage for the four parameters, an agent has enough to call it correctly, though the restart/recovery path remains unaddressed.

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

Parameters3/5

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

Schema description coverage is 100%, so all four parameters (including workspace and approvalId) are already documented in the schema, which is the baseline-3 case. The description reinforces the feedId provenance and references the confirmation flow, but adds no syntax or constraints beyond what the schema states.

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?

The description states a specific verb and resource ('Stops a source from adding new conversations to a dataset') and immediately scopes the effect ('What it already added stays'), which distinguishes it from a destructive delete. It also names the sibling used to obtain the required id, so an agent can route correctly without opening schemas.

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?

It implies the usage context (halting a live feed) and points to caliper_source_feeds_list for the feedId, but never states when-not to use it or names the counterpart tool (e.g., caliper_sources_to_dataset) that would re-enable ingestion. The guidance is implied rather than explicit.

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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