Shoot Plan

What to write next in a shot plan draft

shoot_plan_draft_next

Read-only

Says where a draft stands and the one next thing to do, so you can write a plan layer by layer and have each layer checked as you go. It reads the plan you send and never changes it. It returns the layer you have reached, what that layer still lacks as exact plan paths, the questions to put to your human (answer "none" in the plan when none is the honest answer; never invent a detail), the open findings of finished layers with tested fixes, and which recipe fits each scene that has no shots yet. It is quick: call it after every layer or scene. No AI model runs. Input: plan, the draft so far (a dpl.plan/1 object); optionally brief, the same brief you gave shoot_plan_draft_start (it can be used to check the runtime). Output: dpl.draft-next/1, and next_tool, the tool to call next (when the next action is to run the gate, it is shoot_plan_draft_gate). Follow next_tool. The engine's own wording may name its command line: ignore that and follow next_tool, which names the tool to call next and what to send. We don't keep the plan. We log a one-way fingerprint (hash) of it, its size, the tool, the type of client, the result and the time taken. Needs an agent key from a Shoot Plan account. Free, and it does not count toward the account's 3 free projects a month. Plans up to 8 MB and 120 calls a minute (5,000 a day).

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": {
      "plan": "<plan>"
    },
    "name": "shoot_plan_draft_next"
  }
}

Input Schema

Name	Required	Description	Default
`plan`	Yes	The plan itself: a dpl.plan/1 JSON object (not text inside a string). Call shoot_plan_format for the schema links and an example.
`brief`	No	The brief: a dpl.brief/1 JSON object with title, target_runtime_ms (whole milliseconds) and profile ("film", or "short" for a phone or small-crew shoot); optionally logline, thesis, characters, places and, for a short, delivery, kit, people and shoot_window.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 26, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations only declare readOnly and closed-world; the description adds that it never changes the plan, runs no AI model, requires an agent key, is free and excluded from the 3-project quota, and enforces 8 MB / 120-per-minute / 5,000-per-day limits. It even discloses the logging policy (one-way hash, size, tool, client type, result, timing), which is exactly the kind of context annotations cannot carry.

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 purpose in the first sentence and keeps every subsequent clause functional (outputs, routing, privacy, limits). It is long but dense; minor overlap between 'It is quick' and the earlier usage hint keeps it from a 5.

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?

Despite an output schema existing, the description summarizes the return shape (layer reached, missing paths, questions to the human, open findings with tested fixes, recipe per shot-less scene, next_tool) and reinforces the human-answer convention. Nothing needed to invoke or chain it correctly is missing.

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 coverage is 100%, so the baseline is 3; the description earns an extra point by explaining that plan is a dpl.plan/1 object (not a string) and that brief should be the same object passed to shoot_plan_draft_start, where it is used to check runtime.

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 concrete verb+resource: reads a draft plan, reports where it stands and the single next action. It also distinguishes itself from the gate sibling by naming shoot_plan_draft_gate as the possible next_tool, so an agent can place it in the workflow without opening other schemas.

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?

Gives explicit cadence ('call it after every layer or scene') and routing ('Follow next_tool'), plus the dependency on shoot_plan_draft_start for the optional brief. It also pre-empts a wrong turn by telling the agent to ignore command-line wording in the engine output.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Shoot Plan tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?