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Dactic

Recommend new agents

recommend_new_agents
Idempotent

After confirming the user's goal, save a new recommendation iteration containing validated Claude draft proposals from their own skills/context. Optional priorities produce up to three proposals. A proposal never copies an agent or draft the user already has: when their skills are all in use the result is existing_agent_covers with those agents. Returns a background task; poll get_task_status. Monday synthesis is unavailable in this path. Never deploys.

Input Schema

NameRequiredDescriptionDefault
goalYes
prioritiesNo
idempotency_keyNo
target_platformNo
previous_iteration_idNo

Output Schema

NameRequiredDescriptionDefault
statusYes
messageNo
task_idNo
coverageNo
request_idNo
retrieved_atNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior5/5

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

Annotations only mark this as a non-read, idempotent, non-destructive write; the description goes well beyond that by disclosing asynchronous execution ('Returns a background task; poll get_task_status'), the dedupe outcome key ('existing_agent_covers'), the proposal cap of three, and the guarantee that nothing is deployed. These are the operationally important traits an agent needs before calling a write 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?

Four dense sentences, front-loaded with the precondition and the core action before constraints. Minor waste in the unexplained 'Monday synthesis' clause, which reads as internal jargon without context for the reader.

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?

Async return handling and the dedupe result path are covered, and an output schema exists so return shape need not be restated. However, for a five-parameter mutation with 0% schema coverage, the missing explanation of idempotency_key, target_platform, and previous_iteration_id leaves a real gap.

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%, so the description must carry the parameter burden, and it only gestures at goal and priorities. idempotency_key, target_platform, and previous_iteration_id are never mentioned, leaving three of five parameters with no explanation anywhere in the definition.

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?

States a concrete verb and object: save a new recommendation iteration of validated draft proposals derived from the user's own skills/context. That is specific enough to separate it from siblings like recommend_agent or synthesize_agent, though it does not name those siblings explicitly to sharpen the distinction.

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?

Gives a clear precondition ('After confirming the user's goal') and rules out adjacent behaviors ('Never deploys', 'Monday synthesis is unavailable in this path'), which implies which path to take instead. It never explicitly names the alternative tool to use for synthesis or single-agent recommendation, so routing is inferred rather than spelled out.

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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