YouTube content intelligence

Find comparable competitor video outliers, turn packaging patterns into original tests, and read owned-channel click-through and retention results after fixed windows.

Saves you ~5 h / week

What it installs

Agents 3

  • YouTube Intelligence Analyst

    Builds comparable competitor outlier evidence and evaluates owned packaging and retention tests after fixed windows.

  • YouTube Intelligence Reviewer

    Independently reproduces competitor cohorts, outlier calculations, originality boundaries, owned results, and bounded decisions.

  • YouTube content intelligence Quality Reviewer

    Checks primary evidence, domain controls, deliverable completeness, and communication quality, stopping the run when the work is wrong, unsupported, incomplete, or uncertain.

Teams 1

  • YouTube Intelligence Team

    An analyst builds comparable public and owned-channel evidence while a reviewer reproduces outliers, patterns, readbacks, and decision limits.

Workflows 2

  • YouTube competitor outlier review

    Build comparable public channel cohorts, calculate reproducible outliers, extract non-copying packaging patterns, verify them independently, and approve original owned-channel tests.

  • YouTube owned-channel readback

    Load complete owned-channel result windows, separate packaging and retention, review confounders, approve bounded learning, and preserve the exact register patch.

Documents 2

  • YouTube intelligence rules

    The approved competitor cohort, comparable-baseline method, originality boundaries, owned measures, windows, and decision rules.

  • YouTube content intelligence register

    Public competitor snapshots, reproducible outliers, original package tests, fixed owned-channel results, feedback, and approved learning.

Goals 1

  • YouTube packaging learns from comparable evidence

    Use competitor outliers as research inputs and owned-channel analytics as the decision evidence for original packaging and retention learning.

Skills 1

  • youtube-content-intelligence

    Builds comparable competitor cohorts, detects reproducible public outliers, extracts non-copying packaging hypotheses, and evaluates owned-channel packaging and retention after fixed windows.

Schedules 2

  • Review YouTube competitor outliers

    Run the YouTube competitor outlier review on the configured cadence with the YouTube Intelligence Analyst assigned. Snapshot the complete approved public channel cohort, separate comparable format, age, language, topic, duration, and maturity groups, calculate predeclared median-based outliers with raw values and sample sizes, compare winners with ordinary videos, preserve counterexamples and distribution caveats, and prepare only original owned-channel package hypotheses. The YouTube Intelligence Reviewer reproduces material cohort math, pattern evidence, originality, baselines, and fixed test plans before human approval. A successful review records approved evidence and plans only; it never copies, publishes, schedules, or edits a video. ## Professional quality control Objective: complete the recurring YouTube content intelligence operating cycle and deliver a review-ready, evidence-backed result rather than merely report that the schedule ran. Start by fixing the review period, reading the current source records and prior run, confirming required access, and listing missing or contradictory inputs. Execute the bundle's full authored method in order, retaining source, calculation, command, or before/after evidence for load-bearing findings. Separate facts from interpretation, apply supplied policy without inventing thresholds, and stop any branch that requires missing authority or an unconfirmed human rule. Produce the complete named deliverable plus an evidence record, assumptions, exceptions, unresolved questions, and concrete next actions with owners where the method calls for them. Run the workflow's independent verifier checks and fix failures before requesting approval. The task is done only when every requested section and quality criterion passes or a blocker is explicit; silence, inaccessible data, or polished prose is not proof of completion. For prose, verify audience and voice against supplied examples, support every factual claim, and remove generic AI phrasing, filler, canned setup, hollow transitions, inflated language, repetitive tricolons, bullet soup, and uniform cadence. Preserve format-specific load-bearing elements such as the hook, subject line, quoted language, and call to action while making every paragraph earn its place. Reject unsupported claims or fake specificity. The human retains authority over publication, sending, spend, signing, merging, deployment, and other consequential external actions.

  • Read back owned YouTube results

    Check approved YouTube package tests on the configured cadence and start the owned-channel readback only when a human supplied the immutable video id, package versions, publication time, and the relevant fixed window is complete. Retrieve cited YouTube Studio evidence, separate packaging diagnostics, the preselected retention outcome, downstream signals, guardrails, and traffic sources, compare only with a suitable owned baseline, and inspect post-approval edits and confounders. The reviewer reproduces material results before human approval of reuse, keep testing, retire, or unproven. The schedule never edits, removes, republishes, or reproduces a video or changes channel guidance. ## Professional quality control Objective: complete the recurring YouTube content intelligence operating cycle and deliver a review-ready, evidence-backed result rather than merely report that the schedule ran. Start by fixing the review period, reading the current source records and prior run, confirming required access, and listing missing or contradictory inputs. Execute the bundle's full authored method in order, retaining source, calculation, command, or before/after evidence for load-bearing findings. Separate facts from interpretation, apply supplied policy without inventing thresholds, and stop any branch that requires missing authority or an unconfirmed human rule. Produce the complete named deliverable plus an evidence record, assumptions, exceptions, unresolved questions, and concrete next actions with owners where the method calls for them. Run the workflow's independent verifier checks and fix failures before requesting approval. The task is done only when every requested section and quality criterion passes or a blocker is explicit; silence, inaccessible data, or polished prose is not proof of completion. For prose, verify audience and voice against supplied examples, support every factual claim, and remove generic AI phrasing, filler, canned setup, hollow transitions, inflated language, repetitive tricolons, bullet soup, and uniform cadence. Preserve format-specific load-bearing elements such as the hook, subject line, quoted language, and call to action while making every paragraph earn its place. Reject unsupported claims or fake specificity. The human retains authority over publication, sending, spend, signing, merging, deployment, and other consequential external actions.

Folders 1

  • YouTube intelligence

Requirements

What this playbook expects to do its job. Task Machine does not verify these — you decide whether your setup is ready.

  • Public YouTube channel evidence — Provide competitor channel URLs or handles and the approved comparison period. The agents read public video pages and record retrieval dates; missing or inaccessible statistics remain unavailable.
  • Owned-channel analytics exports — For readbacks, provide YouTube Studio exports or screenshots with impressions, click-through, audience retention, watch time, traffic sources, subscriber changes, and publication metadata.

Setup guide

How to Analyze YouTube Content Performance

A practical method for finding comparable competitor outliers, designing original packaging tests, and reading owned click-through and retention results.

Read the setup guide

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Install YouTube content intelligence and run it with approvals.

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