agent4.io

preview_plan

Generate a plan for a goal and return it for review without persisting anything — no temporary storyline, no enrollment, no user affected. Use it to inspect plan quality before trusting the feature in production, or to see how the agent's task constrains the steps.

Returns {plan, backend, warnings}. `warnings` flags machine-detectable smells, notably checklist
items that are the AGENT's own deliverable ("produce a summary") — those can never be ticked off,
because ticking is judged from what the USER provides, so the step would stall forever.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "agent": "<agent>",
      "goal": "<goal>"
    },
    "name": "preview_plan"
  }
}

Input Schema

Name	Required	Description	Default
`goal`	Yes
`agent`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedAug 1, 2026

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations, the description carries the full burden. It discloses the no-persistence side effect, the return shape ({plan, backend, warnings}), and even explains the subtle 'agent's own deliverable' stall risk in warnings. This is exceptionally transparent and goes well beyond the bare minimum.

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?

The description is front-loaded with the most critical fact (no persistence), followed by practical usage guidance, then the return/warnings details. Every sentence adds value, and the structure is clean and scannable.

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

Completeness5/5

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

Given the tool's moderate complexity, the presence of an output schema, and the absence of annotations, the description is complete enough. It covers purpose, usage, side effects, return structure, and a subtle behavioral trap, leaving little ambiguity for an agent.

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?

The schema has 0% description coverage, so the description must compensate. It clarifies that `goal` is the planning objective and that `agent` has a `task` constraining the steps, but it does not specify expected formats (e.g., whether `agent` is an ID or name) or elaborate on `goal` semantics in detail. Partial compensation, not complete.

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 clearly states the tool's verb and resource: 'Generate a plan for a goal and return it for review.' It also distinguishes itself from persistence-related siblings by emphasizing 'without persisting anything' and explicitly listing what it does not do (no temporary storyline, no enrollment, no user affected).

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 provides explicit use cases: 'inspect plan quality before trusting the feature in production' and 'see how the agent's task constrains the steps.' It does not name alternative tools or state when not to use it, so it falls short of a full 5, but the context is clear.

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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