The lifecycle layer over the trend store: what happens to a trend AFTER first capture.
- re-score on re-capture (last-wins; addTrend duplicate branch, score the one mutable
field; provenance + lifecycle untouched; no false-merge via JSON compare). Reverses
R3a's first-sight D3 — that R3a test reconciled to the new behaviour.
- status new/acted/skipped (effectiveStatus/setStatus + act/skip/reset CLI verbs);
rankForBrief EXCLUDES handled trends (a work queue, not an archive).
- seen-log surfacedCount/lastSurfacedAt (markSurfaced, per-day idempotent); the brief
CLI records surfacing on the store AFTER the pure render, unless --no-mark.
- render: entry id in backticks (copy-paste for act/skip) + · sett Nx prior-day hint.
- schema v3→v4 (additive lossless); the R3a migration block reconciled to the bump,
the new R3b block committed against SCHEMA_VERSION (breaks the reconcile cycle).
score.ts + item.ts untouched (re-score reuses the R3a capture path). RED-first (two
phase: 16 logic-RED + 4 stub-RED). Gate: Section 16k (6 emitters), TRENDS_TESTS_FLOOR
146→171, ASSERT_BASELINE_FLOOR 99→105. trends 171/171, gate 120/0/0, hook suite 139/139.
Plan: docs/research-engine/{brief,plan}-re-r3b.md (light-Voyage hardened @ c40b937).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011vmzxpsFpc8q19LaogAWLD
137 lines
7.2 KiB
Markdown
137 lines
7.2 KiB
Markdown
# linkedin-trends-store
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Persistent **trend store** — the foundation layer of the research engine
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(retning §5). A topic-tagged, provenance-bearing inventory of trend signals
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captured over time, so the engine accumulates **history** instead of starting
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amnesiac each session.
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Twin of [`scripts/specifics-bank`](../specifics-bank): same deterministic
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store / dedup / query discipline, different dedupe key — a trend is identified by
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its **normalized title+URL**, not by free-text content.
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## Generic by architecture
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Nothing niche-specific lives here. A `TrendRecord` carries free-form `topics`
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tags and a free-form `source` string; *which* topics matter and *which* sources
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to poll are decided upstream (config/profile + the capture agent), never
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hard-coded in this module. The same store serves any niche.
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## Data location
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The store lives under the per-user data dir (M0 data-path convention), so trend
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history survives plugin upgrades/reinstalls:
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```
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${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/trends/trends.json
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```
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`LINKEDIN_STUDIO_DATA` overrides the root. No path is hard-coded in prose.
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## Record shape (minimal generic core)
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```ts
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interface TrendRecord {
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id: string; // sha256(normalized title+url).slice(0,12) — also the dedupe key
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title: string; // headline, verbatim
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url: string; // source URL, verbatim
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source: string; // "tavily" | "websearch" | "manual" | <mcp-name>
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capturedAt: string; // ISO-8601 date — when WE captured it
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publishedAt?: string;// optional source publish date (ISO-8601); distinct from capturedAt, first-sight, never back-filled
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topics: string[]; // query tags; unioned across re-captures
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summary?: string; // optional, verbatim
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score?: TrendScore; // persisted relevance (RE-R3a): { mode, dimensions, composite, priority } — REFRESHED on re-capture (RE-R3b, last-wins)
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status?: TrendStatus; // lifecycle (RE-R3b): "new" | "acted" | "skipped"; absent ⇒ "new"; the brief excludes non-new
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surfacedCount?: number; // seen-log (RE-R3b): distinct days surfaced in a brief; absent ⇒ 0; per-day idempotent
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lastSurfacedAt?: string; // seen-log (RE-R3b): ISO date of the most recent surfacing
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}
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```
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`score` is the persisted relevance envelope (RE-R3a): a capture **item** carries the
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agent's **judgment** — `{ mode, dimensions }` (the five 1–10 dimension scores) — and the
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store turns that into the persisted `TrendScore` `{ mode, dimensions, composite, priority }`,
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computing the composite + band once via the single scorer owner (`src/score.ts`). It is
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**refreshed on re-capture** (RE-R3b, last-wins — the timing dimension decays, so the newer
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judgment supersedes the stored one; `score` is the one mutable field, provenance stays
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first-sight); the score-free `add` manual path omits it. The morning brief ranks each bucket
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on `composite` first (schema v4).
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The **lifecycle** fields (RE-R3b) are the trend's life after first capture: `status` is set by
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the `act`/`skip`/`reset` verbs (a freshly-captured trend is implicitly `new`), and the seen-log
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`surfacedCount`/`lastSurfacedAt` is recorded by `brief` (per-day idempotent) so the loop can avoid
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re-surfacing handled work.
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## CLI
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```bash
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# Capture freshly-polled trends — the NORMALIZING BATCH path (the research agent's path):
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# raw items on stdin → validate+normalize each → dedupe on title+url → union topics on
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# re-capture → persist the source's publishedAt → persist the relevance score (when carried).
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# Content-invalid items (incl. a malformed/out-of-range score) are reported in the summary
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# errors[], never fail the run; the summary is {added, duplicates, merged, errors}.
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# An item's "score" carries the agent's judgment (mode + the five 1–10 dimensions); the store
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# computes the composite + band and persists the full TrendScore first-sight.
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echo '[{"source":"tavily","title":"Agentic workflows hit production",
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"url":"https://example.com/agentic","topics":["agents","engineering"],
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"publishedAt":"2026-06-20","summary":"Teams ship multi-step agents past the demo stage.",
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"score":{"mode":"kortform","dimensions":{"pillar":9,"audience":8,"timing":9,"angle":7,"authority":6}}}]' \
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| node --import tsx src/cli.ts capture [--store <path>] [--json]
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# Add a SINGLE trend MANUALLY — raw flags, no normalization, publish-date-free:
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node --import tsx src/cli.ts add \
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--title "Agentic workflows hit production" \
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--url "https://example.com/agentic" \
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--topics "agents,engineering" --source tavily \
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--summary "Teams ship multi-step agents past the demo stage."
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# Topic-scoped history — trends matching these topics, ranked by overlap then recency
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node --import tsx src/cli.ts query --topics "agents,engineering" [--json]
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# Time-scoped history — newest first, optionally windowed/capped
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node --import tsx src/cli.ts list [--since 2026-06-01] [--limit 10] [--json]
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# Dated morning brief — rank the store by composite then pillar-overlap then recency, write a
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# dated Markdown file the SessionStart hook surfaces. Pillars come from the caller (user config).
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# The brief EXCLUDES acted/skipped trends and RECORDS surfacing on the store (per-day idempotent)
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# unless --no-mark. Pillars come from the caller (user config).
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node --import tsx src/cli.ts brief --pillars "agents,engineering" \
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[--fresh-days 7] [--out <dir>] [--no-mark] [--store <path>] [--json]
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# Lifecycle — mark a trend handled so the brief stops re-surfacing it (id shown in the brief / list --json):
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node --import tsx src/cli.ts act --id <id> # wrote about it
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node --import tsx src/cli.ts skip --id <id> # decided to pass on it
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node --import tsx src/cli.ts reset --id <id> # return it to the queue
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```
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Both `capture` and `add` dedupe on normalized title+url — re-capturing the same trend
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never appends a duplicate, it only unions any new topics in.
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## Morning brief (RE-R2b)
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`brief` is the dated, surfaced read over the store (distinct from `query`/`list`, which are
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interactive dumps). It ranks the store against the user's pillars — overlap desc, then
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`publishedAt ?? capturedAt` recency — buckets into top (2+ pillars), single (1 pillar), and
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older (matched but outside the freshness window, default 7 days), and writes:
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```
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${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/trends/morning-brief/YYYY-MM-DD.md
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```
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The file's YAML frontmatter carries a single-line `summary` the SessionStart hook surfaces
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verbatim (zero-tsx — it reads the Markdown, never the TS CLI). As of RE-R3a the brief ranks
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each bucket on the persisted relevance **composite first** (then pillar-overlap, then recency);
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a scored entry shows `· <priority> (<mode>)` and the summary names the top entry's band.
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As of **RE-R3b** the brief is a **work queue**: it **excludes** `acted`/`skipped` trends, shows
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each entry's `id` in backticks (copy-paste-ready for `act`/`skip --id`), flags a re-surfaced item
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with `· sett Nx` (prior-day count, ≥2), and — unless `--no-mark` — **records surfacing** on the
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store (`surfacedCount`/`lastSurfacedAt`, per-day idempotent) after the pure render. An autonomous
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nightly trigger and a brief-history diff remain later slices.
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## Tests
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```bash
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cd scripts/trends
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npm install
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npm test # deterministic store: normalize/id, load/save, dedup+union, query, history
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npm run build
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```
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