skills/alignment-values-north-star/SKILL.md
Creates actionable alignment frameworks that give teams a shared North Star (direction), values (guardrails), and decision tenets (behavioral standards). Enables autonomous decision-making while maintaining organizational coherence. Use when starting new teams, scaling organizations, defining culture, establishing product vision, resolving misalignment, creating strategic clarity, or when user mentions North Star, team values, mission, principles, guardrails, decision framework, or cultural alignment.
npx skillsauth add lyndonkl/claude alignment-values-north-starInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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The framework has three layers: North Star (aspirational direction), Values/Guardrails (core operating principles), and Decision Tenets/Behaviors (concrete, observable demonstrations of values).
Quick Example:
# Engineering Team Alignment
## North Star
Build systems that developers love to use and operators trust to run.
## Values
- **Simplicity**: Choose boring technology that works over exciting technology that might
- **Reliability**: Every service has SLOs and we honor them
- **Empathy**: Design for the developer experience, not just system performance
## Decision Tenets
When choosing between options:
✓ Pick the solution with fewer moving parts
✓ Choose managed services over self-hosted when quality is comparable
✓ Optimize for debuggability over micro-optimizations
✓ Document decisions (ADRs) for future context
## Behaviors (What This Looks Like)
- Code reviews comment on operational complexity, not just correctness
- We say no to features that compromise reliability
- Postmortems focus on learning, not blame
- Documentation is part of "done"
Copy this checklist and track your progress:
Alignment Framework Progress:
- [ ] Step 1: Understand context
- [ ] Step 2: Choose framework
- [ ] Step 3: Develop alignment artifact
- [ ] Step 4: Validate quality
- [ ] Step 5: Deliver and socialize
Step 1: Understand context
Gather background: team/organization (size, stage, structure), current situation (new team, scaling, misalignment, crisis), trigger (why alignment needed NOW), stakeholders (who needs to align), hard decisions (where misalignment shows up), and existing artifacts (mission, values, culture statements). This ensures the framework addresses real needs.
Step 2: Choose framework
For new teams/startups (< 30 people, defining identity from scratch) → Use resources/template.md. For scaling organizations (existing values need refinement, multiple teams, need decision framework) → Study resources/methodology.md. To see examples → Review resources/examples/ (engineering-team.md, product-vision.md, company-values.md).
Step 3: Develop alignment artifact
Create alignment-values-north-star.md with: compelling North Star (1-2 sentences, aspirational but specific), 3-5 core values (specific to this team, not generic), decision tenets ("When X vs Y, we..."), observable behaviors (concrete examples), anti-patterns (optional - what we DON'T do), and context (optional - why these values). See Common Patterns for team-type specific guidance.
Step 4: Validate quality
Self-check using resources/evaluators/rubric_alignment_values_north_star.json. Verify: North Star is inspiring yet concrete, values are specific and distinctive, decision tenets guide real decisions, behaviors are observable/measurable, usable for decisions TODAY, trade-offs acknowledged, no contradictions, distinguishes this team from others. Minimum standard: Score ≥ 3.5 (aim for 4.5+ if organization-wide).
Step 5: Deliver and socialize
Present completed framework with rationale (why these values), examples of application in decisions, rollout/socialization approach (hiring, decision-making, onboarding, team meetings), and review cadence (typically annually). Ensure team can recall and apply key points.
For technical teams:
For product teams:
For company-wide values:
For crisis/change:
Do:
Don't:
resources/template.mdresources/methodology.mdresources/examples/engineering-team.md, resources/examples/product-vision.md, resources/examples/company-values.mdresources/evaluators/rubric_alignment_values_north_star.jsonOutput naming: alignment-values-north-star.md or {team-name}-alignment.md
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.