77655c298c
Phase 8 Production Hardening with complete governance infrastructure: - Vault integration with tiered policies (T0-T4) - DragonflyDB state management - SQLite audit ledger - Pipeline DSL and templates - Promotion/revocation engine - Checkpoint system for session persistence - Health manager and circuit breaker for fault tolerance - GitHub/Slack integrations - Architectural test pipeline with bug watcher, suggestion engine, council review - Multi-agent chaos testing framework Test Results: - Governance tests: 68/68 passing - E2E workflow: 16/16 passing - Phase 2 Vault: 14/14 passing - Integration tests: 27/27 passing Coverage: 57.6% average across 12 phases Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
101 lines
2.9 KiB
Markdown
101 lines
2.9 KiB
Markdown
# Context Checkpoint Skill
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## Overview
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The checkpoint skill preserves session context across token resets and orchestrates sub-agent calls with minimal token usage.
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## Commands
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### Create Checkpoint
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```bash
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/opt/agent-governance/bin/checkpoint now [--notes "description"]
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```
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Captures current state: phase, tasks, dependencies, variables, recent outputs.
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### Load Checkpoint
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```bash
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/opt/agent-governance/bin/checkpoint load [checkpoint_id]
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```
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Loads latest or specific checkpoint. Use `--json` for machine-readable output.
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### Compare Checkpoints
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```bash
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/opt/agent-governance/bin/checkpoint diff [--from ID] [--to ID]
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```
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Shows changes between checkpoints (phase, tasks, variables, dependencies).
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### List Checkpoints
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```bash
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/opt/agent-governance/bin/checkpoint list [--limit N]
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```
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Lists available checkpoints with timestamps and token counts.
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### Context Summary
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```bash
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/opt/agent-governance/bin/checkpoint summary --level minimal|compact|standard|full
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```
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Generates token-aware summaries:
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- `minimal` (~500 tokens): Phase + active task + agent
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- `compact` (~1000 tokens): + pending tasks + key variables
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- `standard` (~2000 tokens): + all tasks + dependencies
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- `full` (~4000 tokens): Complete context for complex operations
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### Auto-Orchestrate Mode
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```bash
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/opt/agent-governance/bin/checkpoint auto-orchestrate --model minimax|gemini|gemini-pro \
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--instruction "command1" --instruction "command2" [--dry-run] [--confirm]
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```
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Delegates commands to OpenRouter models with automatic checkpointing.
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### Instruction Queue
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```bash
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/opt/agent-governance/bin/checkpoint queue list|add|clear|pop [--instruction "..."] [--priority N]
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```
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Manages pending instructions for automated execution.
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### Prune Old Checkpoints
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```bash
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/opt/agent-governance/bin/checkpoint prune [--keep N]
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```
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Removes old checkpoints, keeping the most recent N (default: 50).
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## When to Use
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1. **Before complex operations**: Create checkpoint to preserve state
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2. **After session reset**: Load checkpoint to restore context
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3. **Sub-agent calls**: Use `summary --level compact` to minimize tokens
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4. **Debugging**: Use `diff` to see what changed between checkpoints
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5. **Automated mode**: Use `auto-orchestrate` for humanless execution
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## Examples
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```bash
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# Save current state before risky operation
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checkpoint now --notes "Before database migration"
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# Restore after context reset
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checkpoint load
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# Get minimal context for sub-agent
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checkpoint summary --level minimal
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# Run automated commands with Minimax
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checkpoint auto-orchestrate --model minimax \
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--instruction "run tests" \
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--instruction "deploy if tests pass"
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# Queue instructions for later
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checkpoint queue add --instruction "backup database" --priority 10
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checkpoint queue list
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```
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## Integration
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Checkpoints are stored in:
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- `/opt/agent-governance/checkpoint/storage/` (JSON files)
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- DragonflyDB `checkpoint:latest` key (fast access)
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Audit logs go to:
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- SQLite: `orchestration_log` table
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- DragonflyDB: `orchestration:log` list
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