Curation v2 step 5: deep assessment, utility, diversified shortlist
assess.rs replaces score.rs (DEEP_INSTRUCTIONS, representative sample with [BEGINNING]/[MIDDLE]/[END], facets, cached deep rows with --rescore bypass), rank.rs adds the utility blend over present signals with gate ramps and the leader-clustered shortlist (cap 2 → 3 → uncapped, protected top-N, exploration reserve), editor.rs replaces select.rs with the §13 rendering and utility-ordered fallbacks. ScoredArticle is gone; Candidate is the only flow type. deep_batch_size replaces score_batch_size. Started by Codex (cut off by its usage limit mid-verification) and finished by a Claude agent from docs/plans/curation-v2-briefs/step5.md; reviewed against plan §12–§13. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01A1rCLQeKBgnBo3oTgHuTMe
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Claude Fable 5.1
@@ -4,9 +4,10 @@ A personalized daily newspaper, delivered as an EPUB.
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Every morning a systemd timer wakes one Rust binary. It pulls the last ~26 hours
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from a self-hosted [Miniflux](https://miniflux.app), deduplicates and extracts
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the articles, enriches them with HackerNews/Lobsters/Reddit social proof, filters
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300–500 candidates down to ~120 with cheap heuristics, asks DeepSeek to score them,
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and hands the shortlist to Claude Opus 5 — the editor — which assembles the issue
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the articles, enriches them with HackerNews/Lobsters/Reddit social proof, has
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DeepSeek triage every eligible opening and closely assess a 120-article union,
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then utility-ranks and diversity-caps a 60-item shortlist for Claude Opus 5 — the editor —
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which assembles the issue
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(no minimum size, a hard ceiling), writes a one-line *why* under every headline,
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the summaries and *The Brief*. It assembles two EPUB editions (a standard one
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and one tuned for the Xteink X4 e-ink reader), converts the X4 edition to XTC, and
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@@ -29,7 +30,8 @@ hard spend limits in the providers' dashboards as the real backstop.
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```
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Miniflux ingest ─▶ dedupe ─▶ extraction ─▶ persist ─▶ social enrichment
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─▶ hygiene ─▶ embeddings (Voyage) + cheap signals ─▶ pre-filter ─▶ scoring (DeepSeek)
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─▶ hygiene ─▶ embeddings (Voyage) + cheap signals ─▶ triage (DeepSeek)
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─▶ union admission ─▶ deep assessment (DeepSeek) ─▶ utility + diversity
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─▶ editor (Claude) ─▶ comments ─▶ editorial (Claude)
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─▶ world briefing ─▶ EPUB (standard + X4) ─▶ XTC ─▶ publish ─▶ report
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```
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@@ -56,7 +58,7 @@ fallback (`fallbacks = "default"`) is enabled on every editor request.
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| Rust (2024 edition toolchain) | building | `cargo build --release` |
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| **Miniflux** with an API key | the only content source | Settings → API Keys. The client is read-only and never mutates read state. |
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| **DeepSeek API key** | scoring, and the fallback for every editor call | <https://platform.deepseek.com>. Optional: `--skip-llm` runs the whole pipeline without it. |
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| **DeepSeek API key** | triage and deep assessment, and the fallback for every editor call | <https://platform.deepseek.com>. Optional: `--skip-llm` runs the whole pipeline without it. |
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| **Anthropic API key** | the editor: selection, summaries, The Brief, the weekly profile rebuild | <https://console.anthropic.com>. Optional: without it every editor call runs on DeepSeek. Set a dashboard spend limit; `anthropic.max_daily_usd` is only a runaway guard. |
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| **Voyage AI API key** | article and interest embeddings behind the learned ranking signals | <https://www.voyageai.com>. Optional: without it (or with `--skip-embeddings`) the run uses cached vectors only and the learned signals are absent, never a penalty. |
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| A 32+ byte random secret | signs the article rating links | `openssl rand -hex 32` |
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@@ -106,11 +108,13 @@ does not advance the ingest watermark. It prints the lineup and the cost report.
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`explain` answers "why was this (not) in the paper" from the `candidate_runs`
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row the run persisted for every considered article: the stage it reached and the
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reason it stopped, every raw and normalized signal with its presence and
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effective weight, the top interests, the nearest rated neighbours, any cached
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LLM assessments, and the editor's reason for a pick. `--url` canonicalizes the
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address; an article that is not in the database at all is reported as never
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ingested (a feed problem, not a ranking one). `--near-misses` lists the highest
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ranked articles that were not selected.
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effective weight, the top interests, the nearest rated neighbours, the triage
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and deep assessments (quality, fit, category, rationale, facets), utility and
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rank, the cluster it landed in and what suppressed it, and the editor's reason
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for a pick. `--url` canonicalizes the address; an article that is not in the
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database at all is reported as never ingested (a feed problem, not a ranking
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one). `--near-misses` lists the highest-utility articles that were not selected
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(by preliminary blend for articles the ranker never reached).
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`features backfill` embeds the rated and published articles first (the learned
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set), then the standing interests, then — only with `--all` — every other
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@@ -159,9 +163,9 @@ Secrets belong in the environment file, never in the TOML.
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| `deepseek.base_url` | `https://api.deepseek.com/v1` | OpenAI-compatible endpoint. |
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| `deepseek.model` | `deepseek-v4-flash` | Verified 2026-08-15 (DeepSeek-V4-Flash-0731). |
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| `deepseek.api_key` | — | **`DAILY_EPUB_DEEPSEEK__API_KEY`**. Absent ⇒ the run curates heuristically. |
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| `deepseek.score_batch_size` | `12` | Articles per stage-A scoring request. |
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| `deepseek.deep_batch_size` | `8` | Articles per close-reading assessment request. The removed `score_batch_size` key is a startup error. |
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| `deepseek.triage_batch_size` | `25` | Articles per first-pass triage request. |
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| `deepseek.max_concurrent_requests` | `4` | Triage and stage-A batches in flight at once; the budget is checked before each is spawned. |
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| `deepseek.max_concurrent_requests` | `4` | Triage and deep-assessment batches in flight at once; the budget is checked before each is spawned. |
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| `deepseek.score_temperature` | `0.3` | Scoring temperature. |
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| `deepseek.editorial_temperature` | `0.8` | Summaries and The Brief, only when DeepSeek is the fallback editor. |
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| `deepseek.price_input_per_mtok` | `0.14` | USD per 1M cache-miss input tokens (cost guardrail arithmetic). |
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@@ -223,9 +227,11 @@ signal is absent. Ratings decay with `rating_half_life_days` (60) over
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`deep_keep` (120), `shortlist_keep` (60), `assessment_reuse_days` (3),
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`semantic_min_words` (300), `exploration_slots` (5), `[curation.ranking.quotas]`
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(`triage` 60 · `interest` 20 · `knn` 20), `[curation.ranking.weights.utility]`
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and `[curation.ranking.diversity]` (`cluster_threshold` 0.85, `per_cluster_cap`
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2, `utility_protected` 10) are validated now and drive the LLM triage, deep
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assessment and diversification stages as they land.
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(`quality` 0.40 · `fit` 0.20 · `knn` 0.15 · `interest` 0.10 · `feed` 0.05 ·
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`triage` 0.05 · `social` 0.03 · `heuristic` 0.02, over the signals present for
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each article of the deep set) and `[curation.ranking.diversity]`
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(`cluster_threshold` 0.85, `per_cluster_cap` 2, `utility_protected` 10) drive
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the LLM triage, deep assessment, utility ranking and diversification stages.
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`[curation.ranking.weights.preliminary]` (`interest` 0.35 · `knn` 0.25 ·
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`heuristic` 0.20 · `feed` 0.10 · `social` 0.10) blends the cheap signals; weights
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are renormalized over the signals present for each article, so they need not sum
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@@ -499,9 +505,9 @@ and database rows, with no network access anywhere.
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server. The stages themselves:
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```text
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miniflux.rs ingest curate/ scoring and selection
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dedupe.rs clustering prefilter, llm, triage, admit, score, select,
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editorial, embedding, signals, telemetry
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miniflux.rs ingest curate/ triage, assessment and selection
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dedupe.rs clustering prefilter, llm, triage, admit, assess, rank,
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editor, editorial, embedding, signals, telemetry
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extract.rs body text profile/ the reader's taste profile
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images/ article images comments.rs discussion chapters
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normalize usable <img> world.rs the world briefing
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@@ -582,5 +588,9 @@ From spec §7, plus what implementation turned up:
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the union of triage, interest, neighbour, exploration, blend and auto-include
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retrievers. `explain` shows the assessment and `admitted_by`. Learned signals
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stay absent until their gates open (8 and 15 ratings respectively).
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- **Deep assessment and diversity are live.** DeepSeek reads a representative
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beginning/middle/end sample, separates editorial quality from reader fit, and
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records descriptive facets. Utility is normalized over the deep set; embedding
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leader clusters cap near-duplicates before the 60-item editor shortlist.
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- **One reader, one issue per day.** There is no multi-user support and no
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weekly/retrospective edition (spec §6).
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