youtube-concept-research

Pack Availability Guard

Before telling the user to run a skill from another project-local pack, check .agents/project.json.enabled_packs. If the target pack is not enabled, recommend npx skillpacks install <pack> instead of the target skill. Global skills are always valid. Skills from this same pack are valid because the current skill is already running from that pack.

YouTube Concept Research

Invoke as $youtube-concept-research.

Report-First Approval Gate

Default to scope-first approval: before synthesized research, inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions in a review alignment page plus a concise conversation summary.

Do not perform synthesized research, rank candidates, make recommendations, or write working packets or canonical deliverables until final compiled YAML approves the research scope. Minimal pre-approval discovery may identify available files, source categories, and open questions; label it as scope evidence, not findings.

After approved research-scope YAML, perform the research and write only the non-canonical working packet defined in the staged workflow. Then update the review alignment page with findings and stop again for feedback-only YAML or final compiled YAML artifact approval before creating or updating canonical research, spec, or task files.

Do not include Recommended next skill, Recommended next command, or downstream routing language. The approval request itself is the next action. Only emit next-skill routing after the approved artifact has been written or updated.

Staged Research Workflow

Use this staged workflow for synthesized research or report outputs that would create or update canonical research, spec, or task files.

1. Stage 1 - Scope discovery and approval. Inspect only enough repository, user, and source context to propose research scope, source plan, assumptions, output paths, and approval questions. Build the review HTML alignment page before synthesized research. The page must render the proposed scope, available source categories, known context, assumptions/confidence, proposed working-packet and canonical output paths, and research-scope approval gates. Stop for final compiled YAML approval of the research scope. Do not perform synthesized research, rank candidates, make recommendations, or write working packets, canonical research, spec, or task files in Stage 1.
2. Stage 2 - Research and artifact review. Only after approved research-scope YAML with no unresolved needs-clarification, unresolved down feedback, or other unresolved negative feedback, perform the synthesized research, run required source/code checks, and write only a non-canonical working packet: flat mode uses research/_working/preliminary-<skill>-research.md; product-path mode uses research/{slug}/_working/preliminary-<skill>-research.md. Replace <skill> with this skill's name value. Raw evidence or search logs may remain as supporting evidence where this skill already requires them, but synthesized deliverables stay in the working packet. Update the review HTML alignment page with the full preliminary packet, evidence matrix, assumptions/confidence register, source coverage gaps, proposed canonical file changes, and artifact approval gates. Stop for either feedback-only YAML or final compiled YAML. Feedback-only YAML revises the working packet and page, then remains in Stage 2.
3. Stage 3 - Finalize approved artifacts. Consume final compiled YAML for artifact approval only when it has no unresolved needs-clarification, unresolved down feedback, or other unresolved negative feedback. Apply approved edits first, archive the working packet to docs/history/archive/YYYY-MM-DD/HHMMSS/<original-working-path>, remove the active working packet, write the approved canonical artifacts to the unchanged output paths below, and convert the alignment page to confirmed with the approval record preserved.

Canonical output paths remain unchanged. Search logs and other supporting evidence remain allowed only where this skill's output contract already requires them.

Evidence And Feedback Handling

Treat user feedback as input to evaluate, not as automatic ground truth.

• For factual, evidentiary, technical, or source-backed claims: verify against available evidence. If the user appears to misunderstand the evidence or states something factually incorrect, push back clearly and cite the evidence. Do not rewrite findings merely to agree.
• For taste, brand, positioning preference, risk appetite, prioritization, or other subjective judgment calls: weigh user feedback heavily and adapt the recommendation unless it conflicts with verified evidence.
• When feedback mixes facts and preference, separate them explicitly: correct the factual part, then incorporate the preference where it is a legitimate judgment call.
• When uncertain, say what is known, what is inferred, and what would change the conclusion.

Inputs

• Required: a video concept, rough title, thesis, audience question, or topic idea.
• Optional --channel <slug>: compare the concept against existing channel evidence under research/youtube/data/<slug>/ and strategy artifacts such as channel audit, portfolio, peer benchmark, positioning, or programming.
• Optional --comparables N: target number of comparable videos to inspect. Default 8, max 20.
• Optional --angle search|browse|packaging|retention|format|all: default all.

Process

1. Parse the concept into:

   • audience job: problem, desire, identity, fear, curiosity, or aspiration served.
   • content promise: what the viewer expects to learn, feel, decide, or see resolved.
   • likely discovery mode: search, browse/home, suggested, Shorts, or community/fandom.
   • adjacent spaces: same topic, same audience job, same format, and counter-positioned angles.
   • constraints: creator fit, product/brand fit, production feasibility, and claims needing external verification.

2. Build a query set. Include direct topic queries, problem/search-intent queries, browse-curiosity phrasings, adjacent-category analogs, and same-format/different-niche examples.

3. Find public comparable videos through YouTube search, available local tooling, or supplied URLs. Include:

   • direct comparables on the same topic.
   • audience-job comparables serving the same viewer need.
   • format comparables with a transferable structure.
   • counter-position comparables that prove a different angle can work.

4. Require yt-dlp for public metadata when video URLs are selected:

   command -v yt-dlp
   

5. Select a transcript Python interpreter. Prefer a workspace-local .venv; create it if missing. Install youtube-transcript-api into .venv only when the import check fails and network access is available.

6. Persist raw evidence under research/youtube/data/<video-id>/:

   • metadata-YYYY-MM-DD.json: raw yt-dlp --dump-json "VIDEO_URL" output.
   • transcript/<video-id>.json: raw transcript JSON when available.
   • transcript/transcript-summary.json: transcript text or failure reason.
   • api/comment-threads-YYYY-MM-DD.json: optional public comments when an already-authorized API path is available.

7. Score each comparable for usefulness, not just raw popularity:

   • views/day or recent momentum.
   • apparent outlier status relative to the channel when public channel evidence is available.
   • title/thumbnail promise clarity.
   • transcript/structure evidence availability.
   • audience overlap with the concept.
   • discovery-mode fit.
   • production feasibility for the user's channel.

8. Analyze market lessons:

   • Packaging: title pattern, thumbnail promise, specificity, stakes, novelty, expectation match, and avoidable clickbait.
   • Search/browse fit: whether the concept should lean toward query satisfaction, curiosity, identity, trend, story, or suggested-video adjacency.
   • Hook and retention: first 30-60 seconds, setup length, proof, tension loops, examples, pattern changes, payoff, and CTA.
   • Format: essay, tutorial, teardown, case study, build-in-public, experiment, challenge, reaction, documentary, interview, Shorts, or hybrid.
   • Audience signal: comment themes only when comments were captured; separate praise, objections, confusion, requests, and noise.

9. Produce 3-5 concept variants. At minimum include the best search-led, browse-led, and differentiated/counter-positioned variants when evidence supports them.

10. Recommend one primary direction and explain what to adapt, avoid, or counter-position. If the evidence is weak, recommend the minimum follow-up research rather than over-committing.

Output

Create the research/youtube/ and research/youtube/data/<video-id>/ directories if they do not exist.

Write:

research/youtube/concept-research-<slug>-YYYY-MM-DD.md

Use this structure:

# YouTube Concept Research - [Concept]

> Concept: [user concept]
> Channel: [slug or not provided]
> Date captured: YYYY-MM-DD
> Evidence: [raw paths and search notes used]
> Angle: search / browse / packaging / retention / format / all

## Evidence Coverage

| Comparable | Type | Metadata | Transcript | Comments | Notes |
|---|---|---|---|---|---|
| [Title](URL) | Direct / audience-job / format / counter-position | Available / Missing | Available / Missing | Available / Missing / Not requested | ... |

## Concept Brief

[Audience job, promise, likely discovery mode, constraints, and claims needing verification.]

## Search And Discovery Map

| Query / surface | Intent | Evidence | Opportunity | Caveat |
|---|---|---|---|---|
| ... | Search / browse / suggested / Shorts / community | ... | ... | ... |

## Comparable Performance Snapshot

| Video | Published | Duration | Views | Likes | Comments | Views/day | Comparable value |
|---|---|---:|---:|---:|---:|---:|---|
| ... | ... | ... | ... | ... | ... | ... | Direct / audience-job / format / counter-position |

## Why These Videos Likely Worked

1. [Hypothesis] - [public evidence]
2. [Hypothesis] - [public evidence]
3. [Hypothesis] - [public evidence]

## Audience Jobs And Market Pattern

[What viewers repeatedly respond to, what category promises are common, and what gaps remain.]

## Packaging Lessons

- **Title patterns**: ...
- **Thumbnail promises**: ...
- **Specificity and stakes**: ...
- **Expectation match risks**: ...

## Hook, Structure, And Retention Lessons

- **Opening 30-60 seconds**: ...
- **Proof and examples**: ...
- **Tension / payoff**: ...
- **CTA / ending**: ...

## Concept Variants

| Variant | Discovery mode | Core promise | Evidence | Risk | Recommendation |
|---|---|---|---|---|---|
| ... | Search / browse / suggested / Shorts / community | ... | ... | ... | ... |

## Recommended Direction

[Primary concept direction, why it is strongest, what to adapt, what to avoid, and how to differentiate.]

## Title And Thumbnail Territories

| Territory | Example title pattern | Thumbnail direction | Evidence | Risk |
|---|---|---|---|---|
| ... | ... | ... | ... | ... |

## Draft Video Architecture

[High-level outline only: hook, setup, proof/examples, turn, payoff, CTA. Do not write a full script unless explicitly asked.]

## Risks Of Copying

[What would be derivative, off-brand, unsupported by evidence, or risky to imitate.]

## Open Questions And Evidence Gaps

[Missing transcript, missing comments, uncertain search demand, absent owner analytics, private metrics unavailable, or factual claims needing independent verification.]

Constraints

• Separate observed public evidence from performance hypotheses and recommendations.
• Do not treat public views as proof of CTR, retention, satisfaction, revenue, subscriber conversion, or profitability.
• Do not infer private YouTube Studio metrics unless the user provides them.
• Do not optimize only for clicks; evaluate title/thumbnail promise against likely watch-time and expectation match.
• Do not invent metrics, transcripts, comments, thumbnail details, rankings, or distribution causes.
• Do not recommend copying another creator's title, thumbnail, hook, format identity, or brand. Translate lessons into differentiated execution.
• Date every search/ranking observation and state personalization, geography, and account caveats.
• When the concept relies on factual, legal, medical, financial, political, or current-event claims, recommend independent source verification outside YouTube.
• Do not bypass login walls, bot protections, access controls, or private YouTube Studio data.
• Archive existing canonical artifacts before replacing them under docs/history/archive/YYYY-MM-DD/HHMMSS/<original-relative-path>.

Approved Artifact Handoff

After an approved synthesized write, explicit write/update mode, or any direct artifact mutation:

• List every created or updated synthesized artifact path in the final response.
• State the verification performed, such as readback, schema/check command, or why no executable verification applies for a Markdown-only strategy artifact.
• Check and report the relevant git status for intended artifacts when the project is a git repository. If intended artifacts are modified or untracked, make the next action shipping, committing, or an explicit dirty-artifact handoff before recommending downstream strategy work.
• Do not imply the research workflow is complete while approved artifacts remain untracked or uncommitted unless the user explicitly asked not to ship.
• If stopping for approval before writing, the approval request remains the next action; do not include downstream routing.

Intent-Aware Routing

Before applying the default ## Next-Skill Routing sequence, classify the user's immediate intent and route to the missing action that best serves that intent:

• Strategy refresh: recommend the missing or stale positioning, programming, portfolio, metrics, or product-media artifact.
• Recording prep: recommend the missing series spec, script, build proof, walkthrough guide, or validation artifact needed before recording.
• Upload prep: recommend packaging, title/thumbnail, description, chapters, or final metadata work before broader strategy work.
• Performance review: recommend metrics, cadence, portfolio, peer benchmark, or owner-analytics export work before new content planning.
• Owner analytics or private/manual platform evidence: route to an explicit manual/guide handoff instead of inventing unavailable metrics.
• Dirty intended artifacts: route to shipping/commit/handoff first, not another creator strategy skill.

Use the default next-skill sequence only when no stronger user intent, missing artifact, manual blocker, or dirty-artifact handoff applies.

Alignment Page

When this skill produces durable deliverables (research, specs, plans, reports, prototypes, or any document output), build a full-depth HTML alignment page following ALIGNMENT-PAGE.md in this skill's directory. Output: alignment/youtube-concept-research-{topic}.html.

Default Shipping Contract

Follow the shared shipping contract convention in CLAUDE.md.