Weekly Digest

Weekly Digest

A research-to-publication pipeline that produces a scored, source-verified industry digest. The workflow has seven phases: init, scoping, research, verification, scoring, output, and presentation.

Phase 0: Init

Read ~/.claude/skills/weekly-digest/settings.json. Two possible states:

State A — file missing, or subjects is empty and file has no version field (fresh install): Run onboarding using the AskUserQuestion tool to collect all setup inputs in a single structured prompt:

AskUserQuestion({
  questions: [
    {
      question: "What topic do you want to track weekly?",
      header: "Topic",
      options: [
        { label: "Agent orchestration", description: "Multi-agent frameworks, enterprise deployments, governance" },
        { label: "Design innovation", description: "Design tools, AI-design convergence, award-winning products" },
        { label: "Climate tech", description: "Clean energy, carbon capture, sustainability startups" },
        { label: "AI regulation", description: "EU AI Act, governance frameworks, copyright disputes" }
      ],
      multiSelect: false
    },
    {
      question: "Any geographic focus for sources?",
      header: "Geography",
      options: [
        { label: "Global (no filter)", description: "Include sources from all regions" },
        { label: "Europe, UK, Asia — not US", description: "Deprioritize American sources" },
        { label: "Europe only", description: "EU and UK sources preferred" },
        { label: "Asia-Pacific", description: "Japan, Korea, China, Singapore, India, Australia" }
      ],
      multiSelect: false
    },
    {
      question: "How many top items should the digest include?",
      header: "Digest size",
      options: [
        { label: "5 items (Recommended)", description: "Good balance of depth and brevity" },
        { label: "3 items", description: "Quick scan, only the best" },
        { label: "10 items", description: "Comprehensive coverage" }
      ],
      multiSelect: false
    },
    {
      question: "Where should output files go?",
      header: "Output",
      options: [
        { label: "output/ (Recommended)", description: "Relative to current working directory" },
        { label: "~/Digests/", description: "Home directory, shared across projects" }
      ],
      multiSelect: false
    }
  ]
})

Adapt the example options to match the user's context if you know it from memory/profile. The user can always pick "Other" to type a custom value for any question.

After receiving answers:

1. Map the topic to a slug for output_prefix (lowercase, hyphenated, no spaces — e.g., "Agent orchestration" → "agent-orch")
2. Map geographic focus to geo_focus (null for "Global", string for others)
3. Parse top_n from the digest size answer (3, 5, or 10)
4. Write the full settings file with all defaults + the new subject:

   { "version": 1, "top_n": 5, "target_candidates": 20, "lookback_days": 7,
     "output_dir": "output", "language": "en",
     "weights": { "novelty": 1, "relevance": 1, "slopiness": 1, "technical": 1, "feasibility": 1 },
     "obsidian_vault": null, "subjects": [{ ... }] }

5. Validate output_dir exists (create if needed) before proceeding.
6. Confirm: "Saved. Run /weekly-digest add [topic] to add more subjects."
7. Proceed to Phase 1 with the newly configured subject.

The same AskUserQuestion pattern should be used for /weekly-digest add — ask topic, geo focus, and confirm the generated slug.

State B — subjects exist, user ran /weekly-digest (no args): Run all subjects sequentially.

When subjects list is empty but version field exists (user cleared subjects intentionally): Don't auto-onboard. Respond: "No subjects configured. Add one with /weekly-digest add [topic]."

For the full settings schema, see settings.example.json in the skill directory.

Configuration

Settings live at ~/.claude/skills/weekly-digest/settings.json.

Settings schema

{
  "version": 1,
  "top_n": 5,
  "target_candidates": 20,
  "lookback_days": 7,
  "output_dir": "output",
  "language": "en",
  "weights": {
    "novelty": 1,
    "relevance": 1,
    "slopiness": 1,
    "technical": 1,
    "feasibility": 1
  },
  "obsidian_vault": null,
  "subjects": [
    {
      "topic": "agent orchestration",
      "geo_focus": "European, UK, Asian — not American",
      "output_prefix": "agent-orch"
    }
  ]
}

All fields except subjects are optional — missing keys use defaults shown above. The output_prefix must be a lowercase hyphenated slug (no spaces).

Managing subjects

• /weekly-digest config — show current settings
• /weekly-digest add [topic] — interactively add a new default subject (ask for geo focus and output prefix)
• /weekly-digest remove [topic] — remove a subject from defaults
• /weekly-digest (no args) — run all default subjects sequentially, producing separate file sets for each
• /weekly-digest [topic] — run a single topic as a one-off (ignores defaults)

Settings reference

Phase 1: Scope

Parse the user's request for:

• Topic (required, or from settings): e.g., "agent orchestration", "quantum computing", "climate tech"
• Geographic focus (optional, or from settings): e.g., "European, UK, Asian — not American". Default: no filter

Auto-detect today's date for file naming (YYYYMMDD format).

If the user gives a vague topic like "AI", push back and ask them to narrow it — broad topics produce generic results.

Phase 2: Research

Run 4-6 parallel WebSearch queries designed to cover different angles of the topic. The goal is target_candidates unique items (default 20). Use lookback_days to scope recency — include month/year in queries for the configured window. Structure searches like this:

If a geographic focus is specified, add geographic terms to queries and add a dedicated regional search. When language is set, prefer sources in that language.

Deduplicate across search results. Aim for diversity — reject a candidate pool that's all from the same source type (e.g., all market forecasts or all press releases). Check that at least 3 of these 6 categories are represented.

If fewer than 15 candidates are found: widen one query by removing the year/month filter and run it again. If still below 15, proceed with what exists and note the shortfall in the raw file header.

Phase 3: Source Verification

Select the top 8-10 candidates for verification using this pre-screening signal: pick items whose search snippets contain at least one of: a specific named person/organization, a specific date, a version number, or a dollar amount. Deprioritize items with exclusively superlative or vague language.

Use WebFetch on primary sources to check for slop indicators:

Red flags (high slopiness score):

• No direct quotes from named people
• No specific dates, deal terms, or technical details
• Narrative-essay structure with no attribution
• "Cherry-picked metrics" with no links to verification
• Future dates presented as fact (speculative content)
• Phrases like "poised to", "set to revolutionize", "game-changing"

Green flags (low slopiness score):

• Named executives with direct quotes
• Specific dates, dollar amounts, version numbers
• Official press releases, government sources, arXiv
• Conference announcements with venues and dates
• Case studies with named customers and metrics

When a secondary source has slop indicators but the underlying story might be real, check the primary source (company blog, official press release, arXiv abstract). Score the best available source, not the worst.

If WebFetch fails (paywall, 403, timeout, empty content): note the failure in scoring notes, score slopiness conservatively at 5 (unknown quality), and move on. Record the failed URL in the failure log.

Phase 4: Scoring

Rate each candidate 0-10 on five parameters:

Slopiness convention: 0 = verified, trustworthy source. 10 = pure slop. The formula inverts it so that low-slop items score higher.