R3 slice (b): the rest of hull #3. The morning brief now reads the temporal axis the R3b seen-log records but the ranking ignored. Two DERIVED signals, computed at brief time from already-persisted fields (publishedAt/capturedAt -> ageDays, surfacedCount), never stored: - first-mover: recent (ageDays <= --first-mover-days, default 2) AND never surfaced on a prior day -> ranked up, badge "first ute". Future-dated (ageDays<0) excluded. - saturation: surfaced on >= --saturation-at (default 3) prior days -> ranked down, badge "mettet (Nx)". Self-surfacing (our seen-log), not market coverage. - warming (1..at-1) keeps the R3b "sett Nx" badge but only at >=2 (contract intact); neutral carries no badge. SB1 derived (no schema bump: SCHEMA_VERSION 4 / BRIEF_SCHEMA_VERSION 1 untouched). SB2 the R3a relevance composite stays the PRIMARY sort key; the temporal rank is a new cmp key after pillar-overlap, before effectiveDate -> re-orders only WITHIN a (composite, overlap) tier. temporalSignal is pure (saturationAt clamped >=1). Prior-day surfacings exclude today (via lastSurfacedAt), so a same-day re-render is byte-identical (caught by the R3c run-daily SC7 regression; fixes a latent R3b prior-day imprecision too). brief CLI gains --first-mover-days / --saturation-at; schedule untouched (nightly uses defaults). Wiring: trend-spotter.md (prose), trend-scoring-modes.md (one-line consumer note), README (## Temporal overlay), gate Section 16m (+6 unconditional -> ASSERT floor 111->117), TRENDS_TESTS_FLOOR 192->216. Counts 29/19/27 unchanged. Zero new files. Gate: Passed 132 / Failed 0; trends 216/216; hook suite 139/139 untouched. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_011vmzxpsFpc8q19LaogAWLD |
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| .. | ||
| src | ||
| tests | ||
| package-lock.json | ||
| package.json | ||
| README.md | ||
| run-daily.sh | ||
| tsconfig.json | ||
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
score?: TrendScore; // persisted relevance (RE-R3a): { mode, dimensions, composite, priority } — REFRESHED on re-capture (RE-R3b, last-wins)
status?: TrendStatus; // lifecycle (RE-R3b): "new" | "acted" | "skipped"; absent ⇒ "new"; the brief excludes non-new
surfacedCount?: number; // seen-log (RE-R3b): distinct days surfaced in a brief; absent ⇒ 0; per-day idempotent
lastSurfacedAt?: string; // seen-log (RE-R3b): ISO date of the most recent surfacing
}
score is the persisted relevance envelope (RE-R3a): a capture item carries the
agent's judgment — { mode, dimensions } (the five 1–10 dimension scores) — and the
store turns that into the persisted TrendScore { mode, dimensions, composite, priority },
computing the composite + band once via the single scorer owner (src/score.ts). It is
refreshed on re-capture (RE-R3b, last-wins — the timing dimension decays, so the newer
judgment supersedes the stored one; score is the one mutable field, provenance stays
first-sight); the score-free add manual path omits it. The morning brief ranks each bucket
on composite first (schema v4).
The lifecycle fields (RE-R3b) are the trend's life after first capture: status is set by
the act/skip/reset verbs (a freshly-captured trend is implicitly new), and the seen-log
surfacedCount/lastSurfacedAt is recorded by brief (per-day idempotent) so the loop can avoid
re-surfacing handled work.
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 → persist the relevance score (when carried).
# Content-invalid items (incl. a malformed/out-of-range score) are reported in the summary
# errors[], never fail the run; the summary is {added, duplicates, merged, errors}.
# An item's "score" carries the agent's judgment (mode + the five 1–10 dimensions); the store
# computes the composite + band and persists the full TrendScore first-sight.
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.",
"score":{"mode":"kortform","dimensions":{"pillar":9,"audience":8,"timing":9,"angle":7,"authority":6}}}]' \
| 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]
# Dated morning brief — rank the store by composite then pillar-overlap then recency, write a
# dated Markdown file the SessionStart hook surfaces. Pillars come from the caller (user config).
# The brief EXCLUDES acted/skipped trends and RECORDS surfacing on the store (per-day idempotent)
# unless --no-mark. Pillars come from the caller (user config).
node --import tsx src/cli.ts brief --pillars "agents,engineering" \
[--fresh-days 7] [--out <dir>] [--no-mark] [--store <path>] [--json]
# Lifecycle — mark a trend handled so the brief stops re-surfacing it (id shown in the brief / list --json):
node --import tsx src/cli.ts act --id <id> # wrote about it
node --import tsx src/cli.ts skip --id <id> # decided to pass on it
node --import tsx src/cli.ts reset --id <id> # return it to the queue
# Autonomous trigger (RE-R3c) — emit/install a daily headless brief. PRINT-FIRST: the tool never runs
# launchctl or the cron table; --install writes only the inert launchd plist file. Deterministic
# (no AI capture — a later slice). Default 07:00; --platform auto → launchd on macOS, cron on Linux.
node --import tsx src/cli.ts schedule --pillars "agents,engineering" \
[--at 07:00] [--fresh-days 7] [--platform auto|launchd|cron] [--install|--uninstall] [--store <path>]
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). As of RE-R3a the brief ranks
each bucket on the persisted relevance composite first (then pillar-overlap, then recency);
a scored entry shows · <priority> (<mode>) and the summary names the top entry's band.
As of RE-R3b the brief is a work queue: it excludes acted/skipped trends, shows
each entry's id in backticks (copy-paste-ready for act/skip --id), flags a re-surfaced item
with · sett Nx (prior-day count, ≥2), and — unless --no-mark — records surfacing on the
store (surfacedCount/lastSurfacedAt, per-day idempotent) after the pure render.
Autonomous trigger + headless entry (RE-R3c)
schedule makes the daily loop closed: it emits — print-first — a launchd plist (macOS) or cron
line (Linux) firing the brief every morning, plus the exact activation command. --install writes only
the inert launchd plist file under ~/Library/LaunchAgents/; the tool never runs launchctl
or the cron table — you run the one printed command. --uninstall prints the removal recipe (and
removes the plist file if present).
Both schedulers invoke one tested headless wrapper, run-daily.sh, which runs the deterministic
brief from a scheduler's profile-less environment: it resolves node (baked NODE_BIN, else
command -v, else common locations), cds into the package so tsx resolves, and appends one compact
line <ISO-ts> exit=<code> <json> to ${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/trends/cron.log.
The nightly run is deterministic-brief-only (C1): it re-renders the brief from the current store
— freshness-aging drops stale trends, surfacedCount accumulates day-over-day — but does not poll
new sources. A double-fire on the same day is a safe no-op (RE-R3b per-day idempotency: byte-identical
.md, surfacedCount not double-counted). The autonomous AI capture step (poll → score → capture
before the brief) plugs into the documented seam in run-daily.sh as a later slice (e); a
brief-history diff is also a later slice.
Temporal overlay (RE-R3d)
The brief applies a derived temporal overlay when it ranks — two signals computed at render time
from already-persisted fields (publishedAt/capturedAt → age, surfacedCount → self-exposure), so
nothing new is stored (SCHEMA_VERSION stays 4) and the signal can never go stale:
- first-mover — recent (
ageDays ≤ --first-mover-days, default 2) AND never surfaced on a prior day. Ranked up; badge· 🥇 først ute. A future-dated trend (ageDays < 0) is excluded. - saturation — surfaced on
≥ --saturation-at(default 3) prior distinct days. Ranked down; badge· 🔁 mettet (Nx). This is self-surfacing ("you keep seeing this") from OUR seen-log — not market coverage (that needs external polling, a later slice). - warming (surfaced 1..at-1) keeps the RE-R3b
· sett Nxbadge, but only at ≥2 (that badge contract is unchanged); neutral (no exposure signal) carries no badge.
Ranking integration: the relevance composite (RE-R3a) stays the primary sort key; the temporal
rank (first-mover↑ / saturated↓) is a new key inserted after pillar-overlap and before the
effectiveDate recency tiebreaker — so the overlay only re-orders within a (composite, overlap)
tier, never overriding relevance. Prior-day surfacings exclude today (via lastSurfacedAt), so a
same-day re-render is byte-identical. Tune per run with --first-mover-days N / --saturation-at N
(the scheduled nightly run uses the defaults).
Tests
cd scripts/trends
npm install
npm test # deterministic store: normalize/id, load/save, dedup+union, query, history
npm run build