← All runbooks
gooseworks-ai / composites-industry-scanner

Industry Scanner

Run a daily or weekly industry intelligence scan for a client by using the client's configured keywords, sources, competitor list, and positioning context. The runbook gathers relevant signals from web search, news, blogs, communities, social media, events, funding, jobs, and reg

agent codexmodel gpt-5.5snapshot python312-uveval programmatic7 stepsv1.0.0

Deploy Industry Scanner to your jetty.io

One-click installs this runbook into a collection on your Jetty account. You can run it from the Spot dashboard, schedule it, or pipe inputs in via the API.

Deploy on jetty.io →View source
The shape of the run

7 steps · start to finish.

  1. 1
    Step 1

    Environment Setup

    ▶
    1. Create the output directory and confirm the client inputs are present.
    2. Resolve client_name, lookback_period, and optional focus_area before collecting sources.
    3. Read clients/<client>/config/industry-scanner.json and clients/<client>/context.md.
    4. Note the current UTC date for output filenames and date-bounded queries.
    mkdir -p /app/results
CLIENT_CONFIG="clients/<client>/config/industry-scanner.json"
CLIENT_CONTEXT="clients/<client>/context.md"
test -s "$CLIENT_CONFIG"
test -s "$CLIENT_CONTEXT"
  2. 2
    Step 2

    Load Client Configuration

    ▶

    Follow the source skill procedure, using configured client context and bounded source collection.

  3. 3
    Step 3

    Collect Industry Signals

    ▶

    Run the configured scans over the selected lookback window. Use the source-specific skills and scripts referenced by the client configuration for blogs, Reddit, social media, news, search, events, funding, jobs, and regulatory updates. Keep each finding tied to its source URL, so

  4. 4
    Step 4

    Normalize and Deduplicate Findings

    ▶

    Convert raw results into a common record shape with `title`, `url`, `source_type`, `published_or_observed_at`, `entities`, `summary`, `relevance`, and `confidence`. Deduplicate by canonical URL first, then by highly similar title and source.

  5. 5
    Step 5

    Analyze Patterns and Prioritize Signals

    ▶

    Cluster findings by competitor movement, customer pain, technology shifts, funding, hiring, events, regulatory changes, partnerships, community discussion, and content trends. Score each cluster for recency, source confidence, fit with the client's ICP, and GTM relevance.

  6. 6
    Step 6

    Generate Briefing and GTM Opportunities

    ▶

    Write `/app/results/industry_briefing.md` with the most important signals, why they matter, and cited source URLs. Then write `/app/results/gtm_opportunities.md` with concrete campaign, partnership, messaging, content, sales, or product-led growth ideas tied back to evidence from

  7. 7
    Step 7

    Iterate on Errors (max 3 rounds)

    ▶

    If collection, normalization, or validation fails, perform up to max 3 rounds of targeted repair: