Kjell Tore Guttormsen
e169c78710
R3 slice 1 (research-deepening). Stop discarding the relevance judgment the
trend-spotter already computes: persist a 4-field TrendScore {mode, dimensions,
composite, priority} on TrendRecord (schema v2->v3, additive lossless migrate),
computed by the existing score.ts composite()+band() (one owner, no new arithmetic),
threaded item->store; then rankForBrief sorts each bucket composite-first (sentinel
-1 for unscored) and renderBrief surfaces "· <priority> (<mode>)" per body entry
(briefSummary shows the band only). First-sight only; mode-blind ranking with the mode
shown so the operator can disambiguate instruments.
- score.ts: TrendScore + requiredDimensions(mode) (ordered) + scoreEnvelope (composes
composite+band; throws on bad dim by contract)
- types.ts: SCHEMA_VERSION 2->3; TrendRecord.score?
- store.ts: TrendInput.score?; addTrend persists first-sight (duplicate keeps it);
migrate comment v1->v2->v3 (logic unchanged, JSON.stringify preserves the field)
- item.ts: TrendItem.score?; normalizeItem validates (non-array score/dimensions + the
mode's five dims in [1,10]) -> structured error never throw, carries validated dims;
itemToInput -> scoreEnvelope (no throw on the capture path; direct call throws by contract)
- brief.ts: composite-primary comparator; band+mode render; exact ranking: descriptor
- cli.ts: capture persists score via itemToInput (doc-only); add/score paths unchanged
- agents/trend-spotter.md Step 4.5: capture batch carries the Step-2 dimensions
- gate: TRENDS_TESTS_FLOOR 104->146; new unconditional Section 16j; ASSERT floor 94->99
Tests: trends 146/146 (RED two-phase: logic-RED store/brief/cli; stub-first then
assertion-RED score/item). Gate green (Passed 114 / Failed 0; 113 checks >= 99).
Hook suite 139/139 untouched. Counts 27/19/29 unchanged. No new source file/agent/command.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01VmHCQjJHUyWwxGAVVjNLgp
116 lines
5.6 KiB
Markdown
116 lines
5.6 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; // optional persisted relevance (RE-R3a): { mode, dimensions, composite, priority } — first-sight, never re-scored
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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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set **first-sight** (never updated on re-capture); the score-free `add` manual path omits it.
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The morning brief ranks each bucket on `composite` first (schema v3). Further fields
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(first-mover timing, status) can still be added in a later slice without breaking the shape.
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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 pillar-overlap then recency, write a dated
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# Markdown file the SessionStart hook surfaces. 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>] [--store <path>] [--json]
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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. An
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autonomous nightly trigger and a seen-log freshness model 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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