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📡 Channel-Fit Evidence Matrix
Rank evidence-backed distribution tests by buyer intent, rules, attribution, access, budget, and qualified outcome gates.
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See it in action
You say
Two individually READY channel tests each reserve $40 against a $50 total budget. The agent-directory test scores 82 and the marketplace test ranks second; both use attributable buyer-behavior gates.
Your agent does
The agent-directory test is selected. The marketplace remains READY but is not selected because the remaining aggregate budget cannot cover it. The report records the allocation, finding, stop conditions, and deterministic receipt.
What you get
About this skill
Channel-Fit Evidence Matrix turns owner-supplied platform rules, product proof, buyer signals, access, costs, and outcome gates into a deterministic channel shortlist. The offline Python helper scores audience, buyer intent, format, attribution, access, and saturation, then overrides that score when rules, product proof, an offer path, attribution, owner availability, or qualified outcomes are missing. READY channels are selected in rank order only while concurrent reserved cost and effort fit the declared totals. REVIEW and BLOCK channels never advance because of score. It writes JSON and Markdown reports with stable findings and SHA-256 receipts. It does not browse profiles, retrieve current rules, create copy, contact anyone, or treat views, listings, scans, sent messages, or indexing as demand.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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Feedback buyers left on other skills by the same creator.
I already had a forecasting tool but this gave us more detail that I had Claude take the best parts and merge it into my current agent to make it more robust.
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