skills/goal-reset-proposal/SKILL.md
--- name: goal-reset-proposal description: Drafts a proposed diff to substacker shared-context/goals.md showing which lines to add, remove, or change based on the quarter's review. Never writes to goals.md directly — writer applies manually. Used once per Growth Strategist review. Trigger keywords: goal reset, goals diff, update goals, goals proposal, rework goals. --- # Goal Reset Proposal ## Workflow ``` After the three questions + bet + kill list are drafted: - [ ] Step 1: Read current goa
npx skillsauth add lyndonkl/claude skills/goal-reset-proposalInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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After the three questions + bet + kill list are drafted:
- [ ] Step 1: Read current goals.md line by line
- [ ] Step 2: For each goal, ask:
- Is it still true?
- Has it been met?
- Is it vestigial?
- Is it inconsistent with this review's conclusions?
- [ ] Step 3: Propose changes as unified-diff block with prose justification
- [ ] Step 4: Keep goals list short — if diff adds >2 goals without removing any, reject and retry
- Goal: {old line}
+ Goal: {new line}
+ Goal: {added goal}
Followed by one paragraph justifying the changes, explicitly naming which review conclusion drove each change.
- Goal: Reach 1,000 subscribers by end of 2026
+ Goal: Reach 500 subscribers by end of Q2; 1,000 by end of Q3 if applied-experiments keeps its lift
- Goal: Publish one post per week
+ Goal: Publish biweekly (7 posts per quarter is the floor); one flagship post per month
+ Goal: By end of Q2, at least 3 posts in a second named section, OR formal decision to consolidate into one section
Justification: the "1000 by EOY" is a year-end abstraction; breaking into Q2/Q3 milestones makes it actionable. The weekly cadence missed 7 of 13 weeks — biweekly is what happens, and writing it down removes the guilt tax. The second-section goal forces the emergence decision rather than letting it drift.
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.