skills/negotiation-alignment-governance/SKILL.md
Creates explicit stakeholder alignment through negotiated working agreements, clear decision rights (RACI/DACI/RAPID), and conflict resolution protocols. Use when stakeholders need aligned working agreements, resolving decision authority ambiguity, navigating cross-functional conflicts, establishing governance frameworks, negotiating resource allocation, defining escalation paths, creating team norms, mediating trade-off disputes, or when user mentions stakeholder alignment, decision rights, working agreements, conflict resolution, governance model, or consensus building.
npx skillsauth add lyndonkl/claude negotiation-alignment-governanceInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Copy this checklist and track your progress:
Negotiation Alignment Governance Progress:
- [ ] Step 1: Map stakeholders and tensions
- [ ] Step 2: Choose governance approach
- [ ] Step 3: Facilitate alignment
- [ ] Step 4: Document agreements
- [ ] Step 5: Establish monitoring
Step 1: Map stakeholders and tensions
Identify all stakeholders, their interests and concerns, current tensions or conflicts, and decision points needing clarity. See Common Patterns for typical stakeholder configurations.
Step 2: Choose governance approach
For straightforward cases with clear stakeholders → Use resources/template.md for RACI/DACI and working agreement structures. For complex cases with multiple conflicts or nested decisions → Study resources/methodology.md for negotiation techniques, conflict mediation, and advanced governance patterns.
Step 3: Facilitate alignment
Create negotiation-alignment-governance.md with: stakeholder map, decision rights matrix (RACI/DACI/RAPID), working agreements (communication, quality, processes), conflict resolution protocols, and escalation paths. Facilitate structured dialogue to negotiate and reach consensus. See resources/methodology.md for facilitation techniques.
Step 4: Document agreements
Self-assess using resources/evaluators/rubric_negotiation_alignment_governance.json. Check: decision rights are unambiguous, all key stakeholders covered, agreements are specific and actionable, conflict protocols are clear, escalation paths defined. Minimum standard: Average score ≥ 3.5.
Step 5: Establish monitoring
Set up regular reviews of governance effectiveness (quarterly), define triggers for updating agreements, establish metrics for decision velocity and conflict resolution, and create feedback mechanisms for stakeholders.
RACI (Most Common):
DACI (Better for Decisions):
RAPID (Best for Complex Decisions):
Advice Process (Distributed Authority):
Product vs Engineering:
Business vs Legal/Compliance:
Centralized vs Decentralized Teams:
Communication Norms:
Decision-Making Norms:
Conflict Resolution Norms:
Decision Rights:
Working Agreements:
Conflict Resolution:
Facilitation:
Red Flags:
Resources:
resources/template.md - RACI/DACI/RAPID templates, working agreement structures, conflict resolution protocolsresources/methodology.md - Negotiation techniques (principled negotiation, BATNA analysis), conflict mediation, facilitation patterns, governance design for complex scenariosresources/evaluators/rubric_negotiation_alignment_governance.json - Quality criteriaOutput: negotiation-alignment-governance.md with stakeholder map, decision rights matrix, working agreements, conflict protocols, escalation paths
Success Criteria:
Quick Decisions:
Common Mistakes:
Key Insight: Explicit governance reduces coordination costs over time. Initial investment in alignment pays dividends through faster decisions, less rework, and lower conflict.
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.