Ad Angle Miner

8 steps · start to finish.

1. 1
   Step 1

   Environment Setup

   ▶

   Create /app/results and verify the collection plan before making network requests. If Apify sources are selected, verify APIFY_API_TOKEN is set; otherwise continue with pasted files and web-search-accessible sources.

   mkdir -p /app/results
   if [ -z "${APIFY_API_TOKEN:-}" ]; then
     echo "APIFY_API_TOKEN not set; skip Apify-only collectors unless pasted evidence is provided."
   fi
   

2. 2
   Step 2

   Intake

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   Capture the product, two to five competitors, ICP, selected data sources, and any angles already tested. Convert the intake into a collection plan with explicit source names, queries, item limits, and skip rules for previously tested angles.

3. 3
   Step 3

   Source Collection

   ▶

   Collect evidence from the selected sources. For Amazon reviews, start `web_wanderer/amazon-reviews-extractor`, poll until the actor succeeds, and fetch the dataset items. For Reddit, use `trudax/reddit-scraper-lite` with keyword searches or subreddit start URLs. For B2B review si

4. 4
   Step 4

   Evidence Normalization

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   Normalize each evidence item into `source_evidence.json` with source type, product or competitor, rating or sentiment where available, text excerpt, URL or file provenance, date if present, and tags for pain, outcome, competitor weakness, objection, or buying trigger.

5. 5
   Step 5

   Angle Extraction

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   Extract candidate angles from repeated buyer language. Preserve exact proof quotes, especially complaints, outcome phrases, and comparison language. Group near-duplicates into a single angle and retain source diversity so one loud thread does not dominate the bank.

6. 6
   Step 6

   Score and Rank Angles

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   Score each angle using evidence volume, intensity of language, source diversity, ICP fit, competitor weakness, and novelty against tested angles. Produce a ranked bank with recommended ad formats such as problem-solution, comparison, founder POV, objection handling, proof-led tes

7. 7
   Step 7

   Iterate on Errors (max 3 rounds)

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   If evidence is thin, scoring is tied, or quotes are not attributable, run targeted follow-up collection for max 3 rounds. Each round must name the missing evidence, the exact query or file to inspect, and the reason the result changes or does not change the ranking.

8. 8
   Step 8

   Write Outputs

   ▶

   Write `angle_bank.md`, `angle_bank.csv`, `source_evidence.json`, `summary.md`, and `validation_report.json` under `/app/results`. The Markdown summary should call out top angles, proof quotes, recommended ad formats, weak or missing data sources, and any angles skipped because th