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Dactic

Deploy agent

deploy_agent
Idempotent

First deployment of your selected saved draft. Call without confirmation_code for a preview, show it to the user and obtain authorization, then repeat the same definition/target with the code. Checks skills, source approvals and existing deploy readiness/billing gates. Returns a background task; poll get_task_status for deployment state. An existing deployment is identified without redeploying.

Input Schema

NameRequiredDescriptionDefault
definition_idYes
target_workspaceYes
confirmation_codeNo

Output Schema

NameRequiredDescriptionDefault
statusYes
messageNo
previewNo
task_idNo
coverageNo
request_idNo
retrieved_atNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare this is a non-read-only but non-destructive, idempotent, closed-world mutation. The description adds real context beyond that: prerequisite checks on skills, source approvals, and readiness/billing gates, plus the fact that it returns a background task rather than a completed deployment. It stops short of describing failure modes, error surfaces, or what the preview contains.

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?

The two-phase confirmation instruction is front-loaded in the first sentence, and the remaining sentences each add a distinct fact (prerequisites, task-based return, idempotent lookup). It is dense but no sentence is filler; a slight trim of the gate list would make it tighter.

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?

With an output schema present, the description needn't explain return values, yet it still tells the agent the result is a background task to poll via get_task_status. For a three-parameter mutation with a mandatory human-approval loop, the main gap is the provenance of definition_id and the expected shape of target_workspace.

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 0%, so the description must carry meaning, and it does fully explain confirmation_code (omit for preview, supply to execute) and implies definition_id is a saved draft and target_workspace is the destination. However, it never says where definition_id comes from or what target_workspace expects as a value, leaving two required parameters partly undocumented.

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 plus a scope constraint: 'First deployment of your selected saved draft,' and clarifies that an existing deployment is identified without redeploying. That contrast separates it from sibling tools like invoke_agent, load_agent, and recommend_agent without requiring the schema to be opened.

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?

Prescribes the exact call sequence: call without confirmation_code for a preview, show the preview to the user, obtain authorization, then repeat with the same definition/target and the code. It also routes follow-up work to get_task_status for polling, so both when-to-use and what-to-do-next are 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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