AI Video Atlas Plan Shots API

openapi: 3.2.0
info:
  title: AI Video Atlas Plan Shots API
  version: 1.0.0
  description: 'AI Video Atlas helps agents get usable AI video in fewer generations (first-try success is the goal; Atlas does not claim a success rate). It has sourced AI video shots (prompt + model + est. cost + creator), workflows by job, and vendor-stated prices per second. Use plan_shots to storyboard and price a whole video (one model per project), refine_shot (alias fix_prompt) to fix a take that came out wrong, find_shot for a described shot, recommend_model for "which model / what cost", get_prices for prices, get_workflow for how-to, whats_new for news. Read atlas://guide for rules: costs are estimates, legacy models are excluded, "not stated" means unknown, and always credit and link the creator. Read-only, free, no key. Use get_guide for sourced per-model prompting guidance (structure, camera language, what to avoid, limits) before writing a prompt for a specific model. Guide: https://aivideoatlas.com/agents/'
  contact:
    url: https://aivideoatlas.com/agents/
servers:
- url: https://mcp.aivideoatlas.com
tags:
- name: Plan Shots
paths:
  /v1/plan_shots:
    get:
      operationId: plan_shots
      summary: 'Goal: a usable take on the first generation, so fewer paid generations per shot'
      description: 'Goal: a usable take on the first generation, so fewer paid generations per shot. First review and rewrite the beat list (see brief_review): Atlas parses briefs with rules, so fix non-shots, missing subjects, placeholder lines and generic coverage before writing prompts. If the user names a model or mode, pass it in model/mode (it is kept for every shot unless the docs rule it out). Returns a GUIDANCE PACKAGE, not final prompts: you (the agent) write each full video prompt yourself from it. Per shot: model + mode decision with reasons, the per-model/per-mode prompt structure and tips, 2-3 credited proven example prompts, capabilities/limits/prices with sources, techniques and director rules (practitioner hints at low weight), required assets with image-gen guidance, an 11-section quality checklist, and a starter draft (starting point only, never paste it as-is). If the user names a model or mode, pass it in model/mode (or keep it verbatim in description): Atlas keeps it for every shot unless the vendor docs rule it out, and explains why in user_named. Write each final prompt as flowing, sectioned prose sentences (subject/action, camera/lens/movement, location/light/color, style, audio), never field labels like speaker_id: or Subject:, and without stock filler phrases. Plan a multi-shot AI video from a plain description (deterministic, built only from Atlas data; no AI generation). Output is staged: decide (model/mode/clip length/aspect/cost with reasons and capability checks), direct (shot list with per-model prompts), assets (every reference/frame with status needs-generation|user-supplied|approved), image_prompts, and steps, which include a STOP: get the user to approve assets before generating any video. Global directives (same X in every shot, vertical, no text, style) apply to all shots; questions and request wording are never planned as shots; an explicit shot count is honored; clips longer than an endpoint''s documented max are split. The description is split into beats (sentences, clauses, and cues like "then", "cut to", "close-up", "wide"). For each beat it returns a shot type; a recommended model endpoint with its current vendor-stated $/s and source; the generation mode to use (t2v, i2v, reference-to-video, start/end frame, v2v, lip sync; only modes the vendor docs confirm) with a one-line reason; image prompts for any input frames, plus a shared character/product reference sheet when shots must match; an adapted prompt built from the best-matching sourced example (credited and linked), an estimated cost (5 s per shot by default), and a how-to workflow when one applies (lip sync, consistent character…). It also returns a total. budget_usd (total) and/or max_per_shot steer it to cheaper supported endpoints; each shot also offers a cheaper alternative with its cost, and the plan says if the budget can''t be met. Use this for "plan / storyboard / make me a video of…" requests; use find_shot for a single shot. Before presenting, adapt the wording to the user''s voice, context and brand (names, tone, product details), but keep the prices, models, modes, clip lengths and tags exactly as returned.'
      parameters: []
      responses:
        '200':
          description: Result
      tags:
      - Plan Shots