Kjell Tore Guttormsen 7a158030b6 feat(linkedin-studio): RE-R2a — item→store capture bridge + publishedAt persistence (schema v1→v2, lossless migrate) [skip-docs]

Closes the research-engine capture loop RE-R1 deferred:
- itemToInput(item, capturedAt): pure envelope→TrendInput bridge in item.ts —
  injects capturedAt, carries publishedAt verbatim; no id, no re-validate
- publishedAt persisted: TrendRecord/TrendInput gain it; addTrend conditional-spread,
  first-sight kept on re-capture (no back-fill). SCHEMA_VERSION 1→2 with a lossless
  forward migrate-on-load: Math.max(onDisk, current) + numeric-typeof coercion
  (string/NaN/absent → current; non-array trends coercion preserved verbatim)
- `capture` CLI: stdin raw item|batch → normalize → bridge → addTrend → saveStore once;
  tally {added,duplicates,merged,errors} from AddResult; content-invalid → errors[],
  exit 2 only on bad stdin; --json summary
- wiring: trend-spotter.md Step 4.5 N×`add` → one normalizing `capture` batch; README
  add/capture framing corrected; test-runner Section 16h (capture wiring, unconditional)
  + floors bumped (trends 62→79, ASSERT 87→90)

TDD: 17 new tests (12 genuinely-RED logic-RED + 5 regression guards), tsc clean,
gate 105/0/0. No version bump (additive, v0.5.2 dev).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VmHCQjJHUyWwxGAVVjNLgp

2026-06-24 11:12:50 +02:00

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linkedin-trends-store

Persistent trend store — the foundation layer of the research engine (retning §5). A topic-tagged, provenance-bearing inventory of trend signals captured over time, so the engine accumulates history instead of starting amnesiac each session.

Twin of scripts/specifics-bank: same deterministic store / dedup / query discipline, different dedupe key — a trend is identified by its normalized title+URL, not by free-text content.

Generic by architecture

Nothing niche-specific lives here. A TrendRecord carries free-form topics tags and a free-form source string; which topics matter and which sources to poll are decided upstream (config/profile + the capture agent), never hard-coded in this module. The same store serves any niche.

Data location

The store lives under the per-user data dir (M0 data-path convention), so trend history survives plugin upgrades/reinstalls:

${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/trends/trends.json

LINKEDIN_STUDIO_DATA overrides the root. No path is hard-coded in prose.

Record shape (minimal generic core)

interface TrendRecord {
  id: string;          // sha256(normalized title+url).slice(0,12) — also the dedupe key
  title: string;       // headline, verbatim
  url: string;         // source URL, verbatim
  source: string;      // "tavily" | "websearch" | "manual" | <mcp-name>
  capturedAt: string;  // ISO-8601 date — when WE captured it
  publishedAt?: string;// optional source publish date (ISO-8601); distinct from capturedAt, first-sight, never back-filled
  topics: string[];    // query tags; unioned across re-captures
  summary?: string;    // optional, verbatim
}

Fields (relevance score, first-mover timing, status) can be added in a later slice without breaking the shape.

CLI

# Capture freshly-polled trends — the NORMALIZING BATCH path (the research agent's path):
# raw items on stdin → validate+normalize each → dedupe on title+url → union topics on
# re-capture → persist the source's publishedAt. Content-invalid items are reported in the
# summary errors[], never fail the run; the summary is {added, duplicates, merged, errors}.
echo '[{"source":"tavily","title":"Agentic workflows hit production",
        "url":"https://example.com/agentic","topics":["agents","engineering"],
        "publishedAt":"2026-06-20","summary":"Teams ship multi-step agents past the demo stage."}]' \
  | node --import tsx src/cli.ts capture [--store <path>] [--json]

# Add a SINGLE trend MANUALLY — raw flags, no normalization, publish-date-free:
node --import tsx src/cli.ts add \
  --title "Agentic workflows hit production" \
  --url "https://example.com/agentic" \
  --topics "agents,engineering" --source tavily \
  --summary "Teams ship multi-step agents past the demo stage."

# Topic-scoped history — trends matching these topics, ranked by overlap then recency
node --import tsx src/cli.ts query --topics "agents,engineering" [--json]

# Time-scoped history — newest first, optionally windowed/capped
node --import tsx src/cli.ts list [--since 2026-06-01] [--limit 10] [--json]

Both capture and add dedupe on normalized title+url — re-capturing the same trend never appends a duplicate, it only unions any new topics in.

Tests

cd scripts/trends
npm install
npm test     # deterministic store: normalize/id, load/save, dedup+union, query, history
npm run build

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