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Autonomous co-pilot — agent formulates goal from natural language, enables lock mode with SessionCopilot reasoning, works until goal is achieved.
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Based on SOC occupation classification
Auto-generates code flow diagrams from multi-language module analysis. Detects when architecture diagrams become stale (code changed, diagram didn't). Supports Python, TypeScript/JavaScript, Rust, and Go out of the box. Use when: creating new modules, reviewing PRs for architecture impact, or checking diagram freshness across polyglot repositories. Generates mermaid diagrams showing imports, dependencies, and module relationships.
Execute multiple independent development tasks in parallel using subprocess isolation. Each task runs in a clean /tmp clone with Recipe Runner code-enforced workflow execution. Proven pattern: 4/5 PRs created successfully in first production use.
Interactive teaching agent for the goal-seeking agent generator and eval system. Provides a structured 14-lesson curriculum covering agent generation, SDK selection, multi-agent architecture, progressive evaluation (L1-L12), retrieval strategies, intent classification, math code generation, self-improvement loops with patch proposer and reviewer voting, and memory export/import.
Development workflow for features, bugs, refactoring. Normally executed as a sub-recipe by dev-orchestrator/smart-orchestrator. Supports direct invocation via recipe runner for standalone use.
Default task orchestrator for all development and investigation work. Classifies tasks, decomposes into parallel workstreams if appropriate, and routes execution through the recipe runner. Replaces ultrathink-orchestrator.
Writing clear, discoverable software documentation following the Eight Rules and Diataxis framework. Use when creating README files, API docs, tutorials, how-to guides, or any project documentation. Automatically enforces docs/ location, linking requirements, and runnable examples.
| name | fleet-copilot |
| version | 2.0.0 |
| description | Autonomous co-pilot — agent formulates goal from natural language, enables lock mode with SessionCopilot reasoning, works until goal is achieved. |
| triggers | ["fleet copilot","copilot mode","work toward goal","keep going until done","autonomous mode"] |
| invocable_by | user |
The agent takes the user's natural language, formulates a goal with definition of done, writes it to the goal file, enables lock mode, and starts working. SessionCopilot reasoning monitors progress on each turn.
/fleet-copilot fix the auth bug and make sure tests pass
/fleet-copilot implement OAuth2 login and create a PR
/fleet-copilot keep going until all the TODOs are done
When this skill is activated:
From the user's natural language, create:
Use the Write tool to create .claude/runtime/locks/.lock_goal:
Goal: [objective from user's words]
Definition of Done:
- [criterion 1]
- [criterion 2]
- [criterion 3]
python .claude/tools/amplihack/lock_tool.py lock
Begin immediately. The LockModeHook uses SessionCopilot to monitor and guide.
Lock mode stops when:
mark_complete)escalate)/amplihack:unlock