creator-metrics-review
Review creator-media performance over time using raw YouTube evidence, portfolio metrics, programming goals, and explicit follow-up decisions
- License 许可
- MIT
- 最近更新
- 2026-11-10
- Stars
- ★ 1
- Forks
- 0
01 前言 Front Matter
- name
- creator-metrics-review
- type
- research
- version
- v0.4
- description
- Review creator-media performance over time using raw YouTube evidence, portfolio metrics, programming goals, and explicit follow-up decisions
- argument-hint
- [channel slug] [--period monthly|quarterly]
- interview_depth
- none
02 资源文件 4
- 参考文档agents/openai.yaml240 B
- 参考文档references/public/output-artifacts.md2.8 KB
- 参考文档references/public/subagents.md5.0 KB
- 参考文档references/public/table-migration.md3.4 KB
03 SKILL.md 正文
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 $pack 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.
Creator Metrics Review
Invoke as $creator-metrics-review.
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.
- 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
reviewHTML 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. - Stage 2 - Research and artifact review. Only after approved research-scope YAML with no unresolved
needs-clarification, unresolveddownfeedback, or other unresolved negative feedback, perform the synthesized research, run required source/code checks, and write only a non-canonical working packet: flat mode usesresearch/_working/preliminary-<skill>-research.md; product-path mode usesresearch/{slug}/_working/preliminary-<skill>-research.md. Replace<skill>with this skill'snamevalue. 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 thereviewHTML 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. - Stage 3 - Finalize approved artifacts. Consume final compiled YAML for artifact approval only when it has no unresolved
needs-clarification, unresolveddownfeedback, or other unresolved negative feedback. Apply approved edits first, archive the working packet todocs/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 toconfirmedwith 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
- Preferred creator context when present:
research/creator-presence/<slug>.md, especially for cross-platform performance, audience/community signals, and stale-positioning checks. - Raw metadata under
research/youtube/data/<slug>/. - Channel audit, portfolio, positioning, programming, series specs, and product-led media map when present.
- Optional prior metrics reviews.
Output
Create the research/youtube/ directory if it does not exist.
Write research/youtube/metrics-review-<slug>-YYYY-MM-DD.md with:
- Period covered and evidence paths.
- KPI table: videos published, views, median views, views/day, views/minute, likes, comments, top-video concentration, transcript coverage.
- Series and pillar performance.
- Portfolio drift: whether videos still match the intended roles.
- Wins, misses, and ambiguous signals.
- Decisions: keep, stop, refresh, investigate, or specify.
- Follow-up tasks routed by execution semantics:
- Strategy/research -> creator-media skills.
- Implementation or repo docs ->
tasks/todo.md. - Human-only platform actions ->
tasks/manual-todo.md. - Recurring review cadence ->
tasks/recurring-todo.md.
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/creator-metrics-review-{topic}.html.
Constraints
- Do not treat one video as a trend.
- State metric gaps explicitly.
- Use the dossier when present as preferred creator context for cross-platform signals; preserve raw YouTube evidence as the source of YouTube performance claims.
- Do not perform external account actions or channel changes.
Default Shipping Contract
Follow the shared shipping contract convention in CLAUDE.md.
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