---
name: batch-record-50-raw-clips-in-one-session
description: "Plan and film 50 short answers in one session. Match each saved clip to its question."
category: Content Factory — Produce
stage: Produce
definitive_article: GAP — to be written
status: needs-work
---

# Batch record 50 raw clips in one session

A busy owner may not have time to film each day. This guide helps you plan one session for 50 short answers. Start with a list of real questions, then keep track of each clip as you go.

**The path:** 50 real questions → Film in groups → Check 50 files → Editor.

**Use this when:** The team has agreed to make a 50-clip batch and has enough real questions to fill it.

## Inputs
- A numbered list of 50 distinct questions, each with a real source and a topic. Use [the topic-planning task](https://local-service-spotlight.github.io/task-library/?task=map-out-one-minute-video-topics-using-topic-wheel#task-map-out-one-minute-video-topics-using-topic-wheel) first if the list is missing.
- A willing speaker who knows the answers; a charged phone, stand, free storage, and a quiet place.
- A planned 2–3 hour block from the source method. Treat this as a planning estimate, not a promise that 50 good answers will fit.
- An approved raw folder, tracker, upload access, and named editor. Note permission and private-content limits before filming.

## First-run prompt

> Help me prepare and reconcile a 50-question filming batch. Use only the real questions and sources I provide. Group and number them, flag duplicates, then match saved takes to questions. Show usable distinct answers out of 50 and list any missing items. Do not treat an extra take as a new answer.

## Steps
1. Number the questions 01–50. Group related ones. Remove duplicates and questions the speaker cannot answer. Fill the gaps from real sources before calling the list ready.
2. Build the tracker before filming: question number, exact question, source, topic, take name, file link, length, review state, next owner. A question number spoken aloud helps, but does not replace this log.
3. Test the camera, storage, light, and microphone. Keep one setup while it works; fix it if light, noise, battery, or framing changes. Use silent checks for agents and record any sound-review gap.
4. Film one answer per file. Say the question number, then follow [one-minute video guide](https://blitzmetrics.com/one-minute-video-guide/): question, answer, and one true example. Aim for 45–90 seconds. Keep simple notes nearby.
5. Work in groups of 10–15, then take a short break. Check that those files saved and that the speaker still has clear answers. A rough word is fine; an incorrect answer or failed recording needs another take.
6. Track each take as you go. Mark a replacement take clearly and keep the original until the editor has the safe copy. Do not invent filler questions or accept bad clips just to reach 50.
7. Upload to a batch folder named YYYY-MM-DD-batch-NN-topic within the existing raw folder. Keep one final candidate per question and link any alternate take. Confirm uploads finished.
8. Reconcile the question list against the tracker and saved files. Count distinct answered questions, not file count. Fifty files with three repeated questions is only 47 distinct answers.
9. Hand the checked batch and the exception list to [Upload the source to Drive and Descript](https://local-service-spotlight.github.io/task-library/?task=step-1-upload-video-to-google-drive-and-descript#task-step-1-upload-video-to-google-drive-and-descript). If only 47 pass, record 47 of 50 and the three missing items. The run is partial; make a new filming plan rather than claim completion.

## Definition of done (QA checklist)

- [ ] 50 distinct sourced questions have 50 usable mapped takes; duplicates and abandoned takes are excluded from the count.
- [ ] Each selected take has a clear answer, usable picture and sound, and permission notes.
- [ ] Every selected take is uploaded, linked in the tracker, and accessible to the editor.
- [ ] Any shortfall is counted and named. One session and the planned batch size describe the goal, not permission to hide failed work.

## Example(s)

**Fictional teaching example — not a real batch.** Maple Cycle plans 50 answers: 20 about booking a visit, 15 about shop services, and 15 about buying a used bike. Each question has a sample source note.

The teaching checklist starts with:

| Question | Topic | Selected take | Check |
| --- | --- | --- | --- |
| 01: Do I need a booking? | Visits | `q01-take1.mp4` | 58 seconds; clear answer |
| 02: Can I send a photo first? | Visits | `q02-take2.mp4` | 65 seconds; replaces an interrupted take |
| 03: When will I get a quote? | Quotes | No usable take | The answer gave an unsupported promise |

In this sample, 47 of 50 distinct questions pass. The useful result is a 47-item handoff plus three named gaps. It is not “50 done,” even if the folder holds 54 files. A real run needs the full 50-row list, real file links, and review evidence.

## Handoff and Content Factory context

The editor gets the batch folder, 50-row question list, selected takes, rights notes, and exact pass/shortfall count. [Upload the source to Drive and Descript](https://local-service-spotlight.github.io/task-library/?task=step-1-upload-video-to-google-drive-and-descript#task-step-1-upload-video-to-google-drive-and-descript) starts processing the accepted footage; the speaker owns any agreed missing takes.

This task serves **Produce** in the [Content Factory](https://blitzmetrics.com/content-factory/). Produce makes or prepares source material. Process edits it, Post puts approved work on a channel, and Promote helps it reach people. Only the steps and handoff above are part of this task.

## When this runs

This is one planned session. Repeat only when the content plan calls for another batch. No fixed repeat rate is established by this task.

## Run with an agent

The agent can prepare the plan, organize allowed files, and check the evidence it can actually access. A person records real stories, supplies permission, or resolves an account step when needed. Save the current state in the project files and tracker. A model name does not create memory, access, a scheduler, or permission to act.

For all agent media checks, keep the player muted and its volume at zero before playback. If that cannot be checked, use captions, metadata, or still frames. Do not claim sound quality was heard when it was not.

## Write up the real run

For every actual attempt, [write the run’s meta article](https://blitzmetrics.com/meta-article-prompt/). Link this exact task and its source revision. State the start, work done, evidence, result, gaps, and next owner. Keep failed, partial, and blocked work visible. Writing the record does not authorize publishing it.

Use one stable execution ID for this task’s actual run. Internal retries, checks, and new versions do not add runs. A separately scoped child task may have its own ID linked to the parent. A teaching example has no real execution ID and must not enter the run count. Follow the [recipe and meta-article guide](https://localservicespotlight.com/meta-articles/) for that distinction.


<!-- factory-layer:start -->

## Factory chain (do not treat this as isolated)

- **Phase:** Produce
- **Importance:** 4/5 `●●●●○` — frequency 4, revenue 3, gating 3 (runs every factory cycle or weekly)
- **Suggested previous station:** `map-out-one-minute-video-topics-using-topic-wheel`
- **Suggested next station:** `record-one-minute-videos`
These stations are generated neighbors, not verified prerequisites or handoffs. Follow the task’s actual Inputs and Handoff sections.
- **Handoff:** Raw files in Content Library `01-Raw/` plus a tracker row (question, date, speaker). Next skill never needs the chat — it needs the files.

## Model routing (same factory, any engine)

- **This task's lane:** `any` — Any capable chat model (Claude, ChatGPT, Grok, Gemini). SOP following, drafts, checklists.
- **Single-engine path:** Use the capable AI app you already have. Check its required tools and access before starting. Pass the actual result and proof to the next task.
- **Optional multi-engine:** A tested local model may draft; a stronger model may review facts and voice. Use supported tools for approved actions. Pick models from observed quality and cost; a model name does not prove it can run this task.
- **Never** store the working state in one vendor's memory. Files in the Content Library are the bridge.

<!-- factory-layer:end -->
## Definitive article & links

- Dedicated canonical article: not mapped in the current task source. Use the owned teaching references below while that article gap is reviewed.
- Exact task: [Batch record 50 raw clips in one session](https://local-service-spotlight.github.io/task-library/?task=batch-record-50-raw-clips-in-one-session#task-batch-record-50-raw-clips-in-one-session)
- Publishing standard: [Article Guidelines](https://localservicespotlight.com/article-guidelines/)
- [One-minute video method](https://blitzmetrics.com/one-minute-video-guide/)
- [Topic Wheel: stories, topics, and offer](https://blitzmetrics.com/topic-wheel/)

## Review and evidence still needed

The contributor status in the source header is preserved. It is not a claim that this draft has been independently accepted or that a real run has passed. The worked example above is for teaching only.
- The source still has no dedicated canonical batch article; existing one-minute and Topic Wheel guides supply the teaching basis.
- A real 50-question list and filming evidence are needed to validate an actual run.