skills/update-analogy-catalog/SKILL.md
--- name: update-analogy-catalog description: Appends an entry to substacker shared-context/analogy-catalog.md when the writer PUBLISHES a post that uses a new analogy. Not invoked on seed or draft — only on publish. Records source, target, post, freshness, mapping, where-it-breaks, and why-it-worked. Prevents silent recycling in future Intuition Builder runs. Use at publish time for any post that contains a non-trivial analogy. Trigger keywords: catalog, analogy catalog, update catalog, publish
npx skillsauth add lyndonkl/claude skills/update-analogy-catalogInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Related skills: Called at publish time after Distribution Translator runs (or on manual trigger). Reads the published post to extract used analogies; writes to shared-context/analogy-catalog.md. Does NOT fire on seed or draft creation.
corpus/published/{section}/).update-analogy-catalog explicitly on a published post.For a newly published post:
- [ ] Step 1: Read the published post file
- [ ] Step 2: Extract non-trivial analogies (present a source-target mapping with mechanical weight)
- [ ] Step 3: For each, determine freshness (new / reused / borrowed)
- [ ] Step 4: For each, extract where-it-breaks if named
- [ ] Step 5: Write one entry per analogy to analogy-catalog.md
- [ ] Step 6: Commit ledger-style entry with date + post reference
Trivial similes don't count ("fast as lightning"). An analogy is non-trivial if:
The writer can manually annotate analogy: true in a post's frontmatter to force inclusion, or analogy: skip to exclude.
fresh: the writer's own analogy, first use. Default.reused: the writer used this analogy in a prior published post. Auto-detected by cross-checking the catalog.borrowed: the analogy came from a named source (Hofstadter, a cited paper). Writer annotates.Append to analogy-catalog.md under the table:
| {source} | {target} | {post-title} | {fresh|reused|borrowed} | {note} |
Also in the "notes" section at the bottom:
## {post-slug} — YYYY-MM-DD
- analogy: {source} → {target}
- freshness: fresh|reused|borrowed
- why it worked: {one-sentence note from the writer or inferred from post context}
- breaks at: {the boundary the writer named in the post, if any}
Event: Writer publishes "Why your embedding search melted at 10pm" on 2026-05-20. The post uses two analogies:
2026-03-03-rag-as-prosthetic-memory (already in corpus/seeds/ earlier).Detection:
thermometer, target retrieval quality metric. Not in catalog. Freshness: fresh.prosthetic memory, target RAG. Already in catalog from a prior post. Freshness: reused. Cross-reference to the prior entry.Catalog update:
| source | target | post | freshness | note | |---|---|---|---|---| | thermometer | retrieval quality metric | Why your embedding search melted at 10pm | fresh | "you need to sense before you can steer" — operational framing | | prosthetic memory (reused) | RAG | Why your embedding search melted at 10pm | reused | sibling to 2026-03-03 post; same frame, new context |
freshness: fresh but flag for writer review.analogy: skip in post frontmatter, respect it.testing
Cluster a conference's event records into a small set of coarse themes with finer sub-clusters, an explicit outlier bucket, and soft (multi-membership) affinities — using the hybrid embed-then-label pipeline (embed abstracts, reduce, density-cluster, then LLM-label the clusters) when embedding libraries are available, and an LLM-reasoned hierarchical fallback when they are not. Embeddings do the grouping; the LLM only names the groups. Conference-agnostic. Use when turning structured event records into a navigable theme map for preference elicitation and scheduling, when you need 6-8 reasonable themes rather than 20 muddy ones, or when overlapping talks must belong to more than one theme. Trigger keywords - theme clustering, cluster talks, embed then label, soft membership, outlier talks, conference themes, topic map.
development
Build a personal conference schedule as a constraint-optimization problem — hard constraints (no time overlap, room-to-room travel time, capacity/registration, the attendee's own must-attends and blackouts) plus a user-owned weighted objective trading interest against breadth, pacing (maximize contiguous free time), and serendipity. Surfaces unbreakable conflicts (two high-value overlapping talks the model cannot rank) as decisions for the human rather than silently picking, and reports what each choice traded away. Conference-agnostic. Use to turn a preference profile plus a theme map into a day-by-day plan, to resolve overlapping sessions, or to balance a packed vs paced schedule. Trigger keywords - schedule optimization, conference schedule, constraint optimization, overlapping talks, contiguous free time, conflict surfacing, packed vs paced.
development
Parse a heterogeneous conference program (markdown, HTML, PDF-derived text, or JSON) into normalized event records with per-field confidence scores and independent classification axes (topic, depth, format, prerequisites, recorded, capacity). Detects the program's format before extracting, treats every inferred field as uncertain (present vs inferred vs missing), and flags thin or missing abstracts so downstream enrichment can target them. Conference-agnostic. Use when ingesting a conference or event schedule into a structured store, normalizing a talk/session list, or extracting per-session metadata with calibrated confidence. Trigger keywords - program ingestion, parse schedule, session extraction, event records, conference program, talk metadata, per-field confidence.
development
Build a personalized preference profile from a small number of well-chosen, cluster-grounded questions instead of a long survey. Represents the person's interests as an uncertainty region over the theme map, picks the single highest-information-gain choice-based question (contrasting real talks from different clusters), balances exploiting known interests against exploring uncertain ones, deliberately injects outlier probes to fight selection bias, and stops as soon as the schedule would be stable. Also elicits the user-owned objective weights and hard constraints. Interactive — runs where it can actually ask the person. Conference-agnostic. Use to turn a theme map into a preference profile, to decide what to ask a conference attendee, or to elicit scheduling priorities. Trigger keywords - preference elicitation, ask few questions, information gain, choice-based questions, selection bias probe, objective weights, attendee preferences.