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Propose an action for approval

propose_action

Queue ONE action for HUMAN APPROVAL — nothing is sent or written until a memory owner approves it in the Agents tab.

The kind that makes this powerful from an AI client: `workspace_write`
creates a record in the memory's own apps once approved — an issue on
the Agile board, a support ticket, a CRM deal, a note. Fields:
target=record title, body=record body, extra.class_name=the app class
(issue/ticket/deal/note/…), extra.properties=a {property: value}
object, extra.relationships=[{type, target_name}].

Outbound kinds (jira_comment, slack_message, gmail_send, …) address
connected external tools; see the API's action registry for their
fields. `memory` is the slug. Requires write scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
kindYes
extraNo
memoryYes
targetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false, idempotentHint=false, destructiveHint=false. The description adds critical behavioral context: nothing is written until human approval, it requires write scope, and it queues exactly ONE action. This meaningfully extends beyond annotations, though rate limits and duplicate-handling are not covered.

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 crucial approval-gate fact in the first sentence, then breaks down parameter semantics cleanly. Slightly dense with the parenthetical registry pointer, but every section earns its place.

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?

Covers the workspace_write kind thoroughly and mentions outbound kinds exist, but leaves their field schemas to an external registry. Output schema exists, so return values needn't be explained, but an agent still lacks a full picture of the kind parameter's valid values.

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 description coverage is 0%, so the description must compensate, and it does — defining target, body, extra.class_name, extra.properties, and extra.relationships for workspace_write. But `memory` is only described as 'the slug' and `kind` semantics rely on 'see the API's action registry', leaving gaps.

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+resource (propose ONE action for human approval) and explicitly clarifies that nothing is executed until approval. This distinguishes it from sibling tools like submit_extraction_from_llm, which appear to execute directly.

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

Usage Guidelines4/5

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

The description clearly states the human-approval gate, defining when this tool applies versus direct-execution alternatives. However, it doesn't explicitly name which sibling to use for non-approval flows or when an agent should skip proposal entirely.

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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