# 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`](../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) ```ts 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" | 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 ```bash # 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 ] [--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] # Dated morning brief — rank the store by pillar-overlap then recency, write a dated # Markdown file the SessionStart hook surfaces. Pillars come from the caller (user config). node --import tsx src/cli.ts brief --pillars "agents,engineering" \ [--fresh-days 7] [--out ] [--store ] [--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. ## Morning brief (RE-R2b) `brief` is the dated, surfaced read over the store (distinct from `query`/`list`, which are interactive dumps). It ranks the store against the user's pillars — overlap desc, then `publishedAt ?? capturedAt` recency — buckets into top (2+ pillars), single (1 pillar), and older (matched but outside the freshness window, default 7 days), and writes: ``` ${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/trends/morning-brief/YYYY-MM-DD.md ``` The file's YAML frontmatter carries a single-line `summary` the SessionStart hook surfaces verbatim (zero-tsx — it reads the Markdown, never the TS CLI). Ranking uses only persisted fields; a persisted relevance score, an autonomous nightly trigger, and a seen-log freshness model are later slices. ## Tests ```bash cd scripts/trends npm install npm test # deterministic store: normalize/id, load/save, dedup+union, query, history npm run build ```