Shoot Plan

Make a call sheet from a plan

shoot_plan_call_sheet

Read-only

Makes the call sheet for a shoot from a plan's schedule: for the whole schedule, or for one shoot day, who is called, where and when, with the set-ups in order. A plan with no schedule has no times, and the call sheet says so rather than inventing any. Input: plan, a dpl.plan/1 object that validates; optionally day, the id of one day in the plan's schedule (a day the plan does not have is refused, and the refusal lists the days it has). Output: dpl.call-sheet/1. No AI model runs; we don't keep the plan. Needs an agent key from a Shoot Plan account, and is free up to 3 projects a month. A project is identified by the plan's work id and title; it counts when this tool first makes a finished document for it that month. shoot_plan_allowance says what is left. Over the limit it answers ALLOWANCE_REACHED: do not retry, a new key will not help, tell your human. A fair-use limit also applies: up to 20 finished-document calls for any one project and 60 for the account each month. To count projects we keep, against your account, a one-way fingerprint (hash) of the project's id and title, the month, how many finished documents were made and when, for 13 months after the end of that 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_call_sheet"
  }
}

Input Schema

Name	Required	Description	Default
`day`	No	Optional: the id of one shoot day in the plan's schedule, for example day1. Leave it out for the whole schedule.
`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.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 26, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Goes far beyond the readOnlyHint annotation: discloses no-AI execution, that the plan isn't stored, the agent-key requirement, the free-tier allowance and 3-projects/month rule, the ALLOWANCE_REACHED failure with explicit 'do not retry' guidance, fair-use caps, a 13-month hashed-fingerprint retention, and 8 MB / rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded, but the back half is a dense wall of billing, retention, and limit details that reads more like legal fine print than call guidance. Every element is arguably relevant, but the density hurts scannability.

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?

For a tool with an output schema (dpl.call-sheet/1) and full schema coverage, the description covers inputs, edge cases, failure modes, and billing context comprehensively. Nothing needed to call 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 schema carries the basics; description adds real semantics: the plan must be a validating dpl.plan/1 object, and day must reference an existing day or the tool refuses with a list of valid days. This enriches beyond the schema.

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 ('Makes the call sheet for a shoot from a plan's schedule') and disambiguates the two scopes (whole schedule vs one shoot day). The output type (dpl.call-sheet/1) is named, distinguishing it from siblings like shoot_plan_shot_list or shoot_plan_shoot_pack.

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?

Clearly explains the input conditions, the whole-vs-single-day distinction, and the edge case of a plan with no schedule. It does not explicitly name an alternative sibling or say when NOT to call it, but the usage context is well defined.

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

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