stakeholder-communication
Effective communication strategies for incidents across all stakeholder groups
SKILL.md
| Name | stakeholder-communication |
| Description | Effective communication strategies for incidents across all stakeholder groups |
id: SKL-stakeholder-STAKEHOLDERCOMMUNICATION name: Stakeholder Communication description: Effective communication during incidents is critical for maintaining trust, managing expectations, and coordinating response efforts. Poor communication can turn a technical incident into a PR crisis. version: 1.0.0 status: active owner: '@cerebra-team' last_updated: '2026-02-22' category: Backend tags:
- api
- backend
- server
- database stack:
- Python
- Node.js
- REST API
- GraphQL difficulty: Intermediate
Stakeholder Communication
Skill Profile
(Select at least one profile to enable specific modules)
- DevOps
- Backend
- Frontend
- AI-RAG
- Security Critical
Overview
Effective communication during incidents is critical for maintaining trust, managing expectations, and coordinating response efforts. Poor communication can turn a technical incident into a PR crisis.
Core Principle: "Communicate early, often, and clearly. Silence creates anxiety."
Why This Matters
- Trust Building: Transparent communication builds customer trust
- Expectation Management: Clear updates reduce customer anxiety
- Coordination: Internal teams stay aligned
- PR Protection: Good communication prevents PR crises
- SLA Compliance: Proper communication supports SLA requirements
Core Concepts & Rules
1. Core Principles
- Follow established patterns and conventions
- Maintain consistency across codebase
- Document decisions and trade-offs
2. Implementation Guidelines
- Start with the simplest viable solution
- Iterate based on feedback and requirements
- Test thoroughly before deployment
Inputs / Outputs / Contracts
- Inputs:
- Incident severity and impact
- Affected services and users
- Root cause information (when available)
- Resolution timeline
- Entry Conditions:
- Incident has been triaged and classified
- Severity level determined
- Communication channels configured
- Outputs:
- Status page updates
- Customer notifications
- Internal stakeholder updates
- Executive summaries
- Postmortem communications
- Artifacts Required (Deliverables):
- Communication templates
- Status page configuration
- Email templates
- Social media guidelines
- Executive summary format
- Acceptance Evidence:
- All stakeholders notified appropriately
- Communication timing meets SLA
- Stakeholder satisfaction > 80%
- Success Criteria:
- Initial notification within SLA time
- Regular updates throughout incident
- Clear resolution communication
- Stakeholder satisfaction > 90%
Skill Composition
- Depends on: Incident Triage, Severity Levels
- Compatible with: Escalation and Ownership, Communication Templates
- Conflicts with: Systems without proper communication channels
- Related Skills:
- 41-incident-management/incident-triage - Initial assessment
- 41-incident-management/severity-levels - Severity determines communication urgency
- 41-incident-management/communication-templates - Standardized communication templates
- 40-system-resilience/postmortem-analysis - Post-incident communication
Quick Start / Implementation Example
- Review requirements and constraints
- Set up development environment
- Implement core functionality following patterns
- Write tests for critical paths
- Run tests and fix issues
- Document any deviations or decisions
# Example implementation following best practices
def example_function():
# Your implementation here
pass
Assumptions / Constraints / Non-goals
- Assumptions:
- Development environment is properly configured
- Required dependencies are available
- Team has basic understanding of domain
- Constraints:
- Must follow existing codebase conventions
- Time and resource limitations
- Compatibility requirements
- Non-goals:
- This skill does not cover edge cases outside scope
- Not a replacement for formal training
Compatibility & Prerequisites
- Supported Versions:
- Python 3.8+
- Node.js 16+
- Modern browsers (Chrome, Firefox, Safari, Edge)
- Required AI Tools:
- Code editor (VS Code recommended)
- Testing framework appropriate for language
- Version control (Git)
- Dependencies:
- Language-specific package manager
- Build tools
- Testing libraries
- Environment Setup:
.env.examplekeys:API_KEY,DATABASE_URL(no values)
Test Scenario Matrix (QA Strategy)
| Type | Focus Area | Required Scenarios / Mocks |
|---|---|---|
| Unit | Core Logic | Must cover primary logic and at least 3 edge/error cases. Target minimum 80% coverage |
| Integration | DB / API | All external API calls or database connections must be mocked during unit tests |
| E2E | User Journey | Critical user flows to test |
| Performance | Latency / Load | Benchmark requirements |
| Security | Vuln / Auth | SAST/DAST or dependency audit |
| Frontend | UX / A11y | Accessibility checklist (WCAG), Performance Budget (Lighthouse score) |
Technical Guardrails & Security Threat Model
1. Security & Privacy (Threat Model)
- Top Threats: Injection attacks, authentication bypass, data exposure
- Data Handling: Sanitize all user inputs to prevent Injection attacks. Never log raw PII
- Secrets Management: No hardcoded API keys. Use Env Vars/Secrets Manager
- Authorization: Validate user permissions before state changes
2. Performance & Resources
- Execution Efficiency: Consider time complexity for algorithms
- Memory Management: Use streams/pagination for large data
- Resource Cleanup: Close DB connections/file handlers in finally blocks
3. Architecture & Scalability
- Design Pattern: Follow SOLID principles, use Dependency Injection
- Modularity: Decouple logic from UI/Frameworks
4. Observability & Reliability
- Logging Standards: Structured JSON, include trace IDs
request_id - Metrics: Track
error_rate,latency,queue_depth - Error Handling: Standardized error codes, no bare except
- Observability Artifacts:
- Log Fields: timestamp, level, message, request_id
- Metrics: request_count, error_count, response_time
- Dashboards/Alerts: High Error Rate > 5%
Agent Directives & Error Recovery
(ข้อกำหนดสำหรับ AI Agent ในการคิดและแก้ปัญหาเมื่อเกิดข้อผิดพลาด)
- Thinking Process: Analyze root cause before fixing. Do not brute-force.
- Fallback Strategy: Stop after 3 failed test attempts. Output root cause and ask for human intervention/clarification.
- Self-Review: Check against Guardrails & Anti-patterns before finalizing.
- Output Constraints: Output ONLY the modified code block. Do not explain unless asked.
Definition of Done (DoD) Checklist
- Tests passed + coverage met
- Lint/Typecheck passed
- Logging/Metrics/Trace implemented
- Security checks passed
- Documentation/Changelog updated
- Accessibility/Performance requirements met (if frontend)
Anti-patterns / Pitfalls
- ⛔ Don't: Log PII, catch-all exception, N+1 queries
- ⚠️ Watch out for: Common symptoms and quick fixes
- 💡 Instead: Use proper error handling, pagination, and logging
Reference Links & Examples
- Internal documentation and examples
- Official documentation and best practices
- Community resources and discussions
Versioning & Changelog
- Version: 1.0.0
- Changelog:
- 2026-02-22: Initial version with complete template structure