Overview
/operation-order is a production command in the Operations category of the Prismatic Platform. It generates military-grade operation orders for complex tasks, translating high-level mission objectives into structured, executable plans that follow established command-and-control methodologies adapted for software engineering operations.
The operation order (OPORD) format is borrowed from military planning doctrine and adapted for the Prismatic Platform's development and operational context. Just as military operations require precise coordination between multiple units operating across different domains, complex platform tasks require structured planning that accounts for dependencies, resource constraints, timing, and contingency handling. The /operation-order command formalizes this planning process, producing documents that eliminate ambiguity and ensure all participants share a common operational picture.
An OPORD generated by this command follows the five-paragraph format: Situation (context and environment), Mission (objective statement), Execution (detailed task breakdown), Administration and Logistics (resource allocation), and Command and Signal (communication and authority). This structure ensures that every operation is planned with the rigor required for successful execution in complex, multi-stakeholder environments.
This command operates under the L3 authority level and is executed by the supreme-coordinator agent. It is part of the platform's 216-command slash command registry, built on the AIAD (Autonomous Intelligence Agent Design) standard. The L3 authority level reflects the command's ability to coordinate resources across multiple platform domains and assign tasks to agents at various authority levels.
Architecture
The /operation-order command implements a structured planning pipeline that transforms high-level objectives into detailed operational documents.
Planning Pipeline
Mission Objective --> Context Analyzer
|
Situation Assessment
|
Mission Formulation
|
+-------- + --------+
| | |
Task Resource Timeline
Decomposer Planner Scheduler
| | |
+---------+---------+
|
Risk Assessor
|
Contingency Planner
|
OPORD Generator
|
Validation EngineCore Components
| Component | Module | Responsibility |
|---|---|---|
| Context Analyzer | PrismaticOps.OPORD.ContextAnalyzer | Platform state and environment assessment |
| Mission Formulator | PrismaticOps.OPORD.MissionFormulator | Objective translation and success criteria |
| Task Decomposer | PrismaticOps.OPORD.TaskDecomposer | Hierarchical task breakdown structure |
| Resource Planner | PrismaticOps.OPORD.ResourcePlanner | Agent and resource allocation |
| Timeline Scheduler | PrismaticOps.OPORD.TimelineScheduler | Phase sequencing and dependency management |
| Risk Assessor | PrismaticOps.OPORD.RiskAssessor | Risk identification and mitigation planning |
| OPORD Generator | PrismaticOps.OPORD.Generator | Document generation in standard format |
OPORD Structure
| Paragraph | Content | Platform Mapping |
|---|---|---|
| 1. Situation | Enemy forces, friendly forces, environment | Current bugs, available agents, platform state |
| 2. Mission | Who, what, when, where, why | Objective, timeline, scope, success criteria |
| 3. Execution | Tasks, coordination, timeline | Task breakdown, agent assignments, phases |
| 4. Admin/Logistics | Support, supply, maintenance | Resources, dependencies, infrastructure |
| 5. Command/Signal | Authority, communication | Agent authority, telemetry, reporting |
Usage
Basic Operation Order
# Generate OPORD for a feature implementation
/operation-order --mission "Implement NIS2 compliance dashboard"
# Generate OPORD for a production deployment
/operation-order --mission "Deploy perimeter MVP to production" --type deployment
# Generate OPORD for incident response
/operation-order --mission "Resolve production performance degradation" --type incidentAdvanced Planning
# OPORD with specific resource constraints
/operation-order --mission "Migrate database schema" --resources "2 agents, 4h window" --risk-tolerance low
# OPORD with timeline constraints
/operation-order --mission "Complete security audit" --deadline "2026-02-28" --phases 3
# OPORD with cross-team coordination
/operation-order --mission "Platform-wide quality uplift" --teams "blue,white,purple" --coordination-level high
# OPORD for multi-milestone operation
/operation-order --mission "M46 to M47 transition" --milestones M46,M47 --dependencies autoOutput and Distribution
# Generate OPORD in markdown format
/operation-order --mission "Feature X" --output markdown --file opord-feature-x.md
# Generate OPORD with GitLab issue creation
/operation-order --mission "Feature X" --create-issues --gitlab-milestone M47
# Generate OPORD with task assignment
/operation-order --mission "Feature X" --assign-agents --auto-dispatchOptions & Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
--mission | String | Required | Mission objective statement |
--type | Enum | feature | Operation type: feature, deployment, incident, maintenance, migration |
--deadline | DateTime | - | Operation completion deadline |
--phases | Integer | Auto | Number of execution phases |
--resources | String | Auto | Resource constraints specification |
--teams | List | Auto | Teams involved in operation |
--risk-tolerance | Enum | medium | Risk tolerance: low, medium, high |
--coordination-level | Enum | standard | Coordination: minimal, standard, high, maximum |
--dependencies | Enum | auto | Dependency resolution: auto, manual, none |
--milestones | List | - | Related GitLab milestones |
--output | Enum | text | Output format: text, markdown, json, html |
--file | Path | - | Write OPORD to file |
--create-issues | Boolean | false | Create GitLab issues from task breakdown |
--gitlab-milestone | String | - | Assign issues to GitLab milestone |
--assign-agents | Boolean | false | Auto-assign agents to tasks |
--auto-dispatch | Boolean | false | Automatically dispatch assigned tasks |
Execution Flow
Phase 1 -- Situation Assessment (0-10s): The Context Analyzer scans the current platform state, including active applications, pending issues, resource availability, and environmental conditions. It identifies constraints, risks, and opportunities that inform the operation plan. This assessment draws from the platform's telemetry, GitLab issues, and quality gate status.
Phase 2 -- Mission Formulation (10-20s): The Mission Formulator translates the high-level objective into a precise mission statement with measurable success criteria. This includes defining the operation's scope, identifying out-of-scope activities, and establishing the commander's intent -- the overarching goal that enables subordinate decision-making when situations deviate from the plan.
Phase 3 -- Task Decomposition (20-40s): The Task Decomposer breaks the mission into a hierarchical task structure. Each task is defined with inputs, outputs, dependencies, estimated duration, required skills, and assigned authority level. Dependencies are resolved into a directed acyclic graph (DAG) that determines execution order.
Phase 4 -- Resource Allocation (40-50s): The Resource Planner maps available agents, tools, and infrastructure to task requirements. It considers agent capabilities, current workload, and authority levels when making assignments. Resource conflicts are resolved through priority-based scheduling.
Phase 5 -- Risk Assessment and Contingency (50-60s): The Risk Assessor evaluates potential failure modes for each phase and task. Risks are rated by probability and impact. For high-rated risks, the Contingency Planner generates specific response plans including fallback procedures, rollback strategies, and escalation paths.
Phase 6 -- OPORD Generation (60-70s): The Generator assembles all planning artifacts into the standard five-paragraph OPORD format, including annexes for detailed technical specifications, communication plans, and timeline visualizations.
Integration Points
| Component | Integration Type | Description |
|---|---|---|
| Prismatic Agents | Execution + Assignment | Managed by supreme-coordinator; assigns tasks to other agents |
| GitLab CI | Issue creation | Creates issues and milestones from task breakdown |
| AIAD Registry | Agent discovery | Queries agent capabilities for task assignment |
| Quality Gates | Gate integration | Embeds quality gates at phase boundaries |
| Telemetry | State assessment | Reads platform telemetry for situation assessment |
| Session Context | Persistence | Stores OPORD in session context for reference |
Best Practices
Mission Clarity: Spend time crafting a precise mission statement. Vague objectives produce vague plans. Good mission statements include the action, the target, the timeline, and the success criteria: "Implement NIS2 compliance scoring for all perimeter assets by February 28 with 90%+ accuracy."
Phase Boundaries: Place quality gates at every phase boundary. Each phase should produce a verifiable deliverable before the next phase begins. This prevents cascading failures from undetected problems in early phases.
Resource Buffers: Plan for 120% of estimated resource requirements. Agent availability fluctuates, tasks encounter unexpected complications, and dependencies may introduce delays. Resource buffers absorb this variability without requiring plan revision.
Contingency Depth: Every OPORD should have at least one contingency plan per critical phase. The contingency should specify the trigger condition, the response action, and the recovery path back to the main plan.
Living Documents: Treat OPORDs as living documents that are updated as the operation progresses. Use version-controlled storage and note deviations from the plan along with their rationale.
Error Handling
| Error Condition | Handling Strategy | User Impact |
|---|---|---|
| Ambiguous mission statement | Clarification requested with examples | Planning paused until clarified |
| Insufficient resources | Warning with resource gap analysis | Plan generated with caveats |
| Circular dependencies detected | Dependency graph restructured | Warning about restructured tasks |
| Deadline infeasible | Timeline analysis with minimum viable plan | Options presented for scope reduction |
| Agent capability mismatch | Alternative assignments suggested | Modified task-agent mapping |
| GitLab API failure | OPORD generated without issue creation | File-based output only |
Advanced Usage
OPORD Templates
Define reusable templates for recurring operation types:
# Create template from existing OPORD
/operation-order --save-template deployment-standard --from opord-deploy-v3.md
# Generate OPORD from template
/operation-order --template deployment-standard --mission "Deploy v7.6.0"
# List available templates
/operation-order --list-templatesMulti-Phase Operations
For large operations spanning multiple sessions:
# Generate phased OPORD with session boundaries
/operation-order --mission "Platform migration" --sessions 5 --phase-per-session
# Resume operation from specific phase
/operation-order --resume opord-2026-02-15 --from-phase 3Doctrine Compliance
All commands operate under the NO MERCY, NO DOUBTS doctrine:
- NO MERCY: Zero tolerance for incomplete execution or quality violations. Every generated OPORD must contain all five paragraphs, all tasks must have assigned resources, and all risks must have mitigation plans. No partial planning. No deferred contingency analysis.
- NO DOUBTS: Full investigation before action, evidence-based results. Situation assessments are grounded in measured platform state, not assumptions. Resource estimates are based on historical performance data. Risk ratings use quantified probability and impact assessments.
Related Commands
- /orchestrate - Revolutionary AI-powered task orchestration with 10x development efficiency
- /archer-supreme - Elite tactical commander for impossible mission execution
- /supreme-coordinator - Supreme coordination across all platform domains
- /agents - List and manage agent ecosystem with status monitoring
- /code - Core coding implementation and feature development
- /fix - Bug fix implementation with mandatory regression tests
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Created by Tomáš Korcak (korczis) | Open Source under GHL