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    voc-listener Pro

    1

    Turn YouTube comments into voice-of-customer signal — from inside your own AI agent.

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    voc-listener Pro

    voc-listener Pro

    Example session with this skill installed

    Sweep the 'freelance-pricing' area for new hits using the regex scorer. Limit the spend to 500 units and show me the estimate first.

    • Read your context and instructions
    • Compiled the voc-listener pro
    • Generated the document

    I have analyzed the 'freelance-pricing' area. The discovery phase found 12 new videos. The sweep will prioritize those with titles matching your 'pricing' and 'rates' vocabulary.

    Estimate:

    • Discovery: 100 units
    • Sweep: ~150 units (12 videos, shallow depth)
    • Wall time: ~2 minutes
    • Budget: 9,450 units remaining today
    • Results will stream live. Stop anytime with Ctrl-C.

    Sweep Results (freelance-pricing)

    ScoreDirectionComment PreviewVideo Source
    88pain"I've been a designer for 3 years but I still feel like I'm guessing every time I send a quote. I'm terrified of overcharging and losing the lead."yt.com/watch?v=551
    74question"How do you handle clients who ask for a discount on the first invoice? I don't want to seem desperate but I need the work."yt.com/watch?v=829
    65pain"The hourly rate trap is real. I finished a project in half the time because I'm fast, and ended up making less money for better work."yt.com/watch?v=312
    42mixed"Switched to value-based pricing last month. It's harder to sell but the margins are finally worth the stress."yt.com/watch?v=551

    Next steps

    • Run inbox --status new to triage these 4 hits.
    • Execute synthesize to draft the pricing struggle report.
    • Adjust topic_terms to include "value-based" for more specific hits.

    voc-listener-pro.pdf

    PDF · document

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Extract raw customer language for high-converting marketing copy.Map competitor weaknesses by analyzing their video comment sections.Generate structured research reports on audience frustrations in any niche.Monitor niche trends by streaming new human struggle hits in real-time.

    About this skill

    Turn YouTube comments into voice-of-customer signal — from inside your own AI agent.

    voc-listener Pro is a portable Python library + agent skill (SKILL.md) that teaches your agent to build its own audience listener: define a question about any niche, sweep YouTube comment threads, and get scored, real-people pain back in minutes — streamed live as JSON.

    Two scoring modes:

    • Regex (default): a zero-inference vocabulary gate. Literally a regex. Free, runs everywhere, no API calls.
    • Clef (optional): a Cloudflare Workers AI decision model that judges comment relevance per video — with calibrated pre-spend token estimates, per-run token budgets, automatic regex fallback if the budget runs out, a per-run usage ledger, and a prescore event before the first token is spent.

    Built for cost discipline: agent-steered focus areas, a daily quota cap with per-run budgets, honest per-area fidelity reporting (tells you when you're spread too thin), and an estimate-first rule — the skill shows the cost before spending a single quota unit.

    You bring your own keys. YouTube Data API v3 key (free) and optionally a Cloudflare account. Everything runs in your environment; the seller never sees your credentials. Stdlib-only Python 3.11+, no pip install, 30 files.

    License: commercial, one-time payment. Perpetual use for you and all agents operating on their behalf. No redistribution or resale. No DRM, no license server, no phone-home.

    Support: dotmakes.things@gmail.com — buyer questions, install help, bug reports.

    Honest limits: YouTube only — a deliberate depth-over-breadth choice: YouTube comments are long-form, where people explain why they struggle; short-form platforms don't carry buying-decision reasoning. (Multi-source is on the roadmap, not in v1.) Battle-tested on real product research passes — ADHD audience analysis plus two audience-intelligence dogfoods, with worked examples linked below. One install serves your whole agent fleet: the license covers you and every agent operating on their behalf, and focus areas let one install track multiple questions at once. The Clef token estimator is calibrated on 47 live calls (2026-10-01, ~11% conservative, zero underestimates) and self-corrects from each run's usage ledger — estimates stay conservative by design, with per-run budgets and automatic regex fallback keeping spend safe.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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