skills/wc-decision-board/SKILL.md
Renders the FIFA World Cup Fantasy decision board — the advisory output that surfaces 2-4 genuinely distinct, weighted options for the expert manager and ends on "your call." Takes the evolution engine's verified offspring (with fitness decomposition, genotype lineage, and specialist dissent) and formats each as an option with its concrete picks, EV/ownership-leverage/variance/progression decomposition, football reasoning, what it's betting on, the dissent, and an ownership read — then a trade-off axis, a recommended-but-overridable default tied to the rank objective, and a "what I need from you." Enforces options-not-commands, shows the working, surfaces dissent, never auto-commits. Use to present any squad/matchday/transfer/chip decision.
npx skillsauth add lyndonkl/claude wc-decision-boardInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Implements footballfantasy/context/frameworks/decision-board-format.md. This is the system's product surface and the structural enforcement of "the agents feed me options, I decide." A board that reads like a command has failed even if its top option is right. The manager is the selection operator; this renders the choice for them.
- [ ] 1. Select the 2–4 offspring to show (spanning the variance spectrum — at least one cover, one climb)
- [ ] 2. Render each as an OPTION (picks + decomposition + reasoning + bet + dissent + ownership read)
- [ ] 3. Write the TRADE-OFF axis (what actually separates them)
- [ ] 4. Write the RECOMMENDED DEFAULT (tied to θ, explicitly overridable)
- [ ] 5. Write WHAT I NEED FROM YOU (the inputs that would sharpen/change the board)
- [ ] 6. End on "your call." Write to boards/ and present. Do NOT proceed past this.
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[DECISION] — [round id] · [phase] · lock [deadline]
Objective: θ=[protect|gain|neutral] (k=[..]) — [one line why]
Mini-league: [standing] · [rounds left] Diversity: [wide|close]
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CONTEXT
[2–4 lines: where we stand, what changed (eliminations, fixture swings,
the field's notable moves), the one tension this decision turns on.]
── OPTION A · "[handle]" ─────────────────────────────────────
Lineage: [A1 captain core + A4 clean-sheet stack + A2 differential pod]
Fitness: [n] · variance [band]
Decomp: xEV [n] · ownership-leverage [+/−n] · progression [n]
Picks: [squad/XI/captain/bench/chip — the concrete plan]
Strength: [2–3 lines, football reasoning the manager can interrogate]
Betting on: [the key assumption that must hold]
Dissent: [the strongest case against — from the critic / specialist verify]
Ownership: [template-covering | balanced | differential-leaning]
── OPTION B · "[handle]" ── [a genuinely different bet — different variance band] ──
…
[C, D as warranted; never more than 4]
THE TRADE-OFF
[1–3 lines naming the axis the manager is choosing on — variance vs floor,
template vs differential, this-round xEV vs progression carry.]
RECOMMENDED DEFAULT
"If you do nothing else, [Option X] — because [one line tied to θ].
If you'd rather [protect/gamble] instead, [Option Y]."
WHAT I NEED FROM YOU
• [the input(s) that would change the board — standing, appetite, non-negotiables, chip intent]
Your call — tell me which option (or your own variant) and I'll lock it and update state.
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Sub-decisions (switch the armband now or bank the 7? fire the Shield or hold? transfer X or Y?) use the same shape compressed to 2 options + trade-off + default + your-call. Same contract at every scale.
boards/YYYY-MM-DD-<decision>.md and return its path; the Director presents and waits.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.