Create checkpoint
AI Context Kit provides a structured, instruction-based framework for context-aware AI collaboration across LLM providers. It includes authoritative specs, canonical templates, and skills workflows for creating and validating user context and project AGENTS.md files.
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Capture the current session state as a checkpoint artifact per spec section 4.4. Use when the user signals session end or explicitly requests a checkpoint. Do not use mid-session or without user approval.
SKILL.md
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Create Checkpoint
Purpose
Capture the active session state as a structured Markdown checkpoint artifact so the session can be restored in a future conversation.
How to Invoke
Load or attach this file's contents into your AI session to activate the workflow (paste, upload, or reference with #file:skills/create-checkpoint/SKILL.md in VS Code Copilot Chat). In Claude Projects, add it to project knowledge. See Invoking Skills in the README for full platform guidance.
When To Use
- When the user signals they are ending the session and want to resume later.
- When the user explicitly requests a checkpoint.
- Do not create checkpoints silently or mid-session without the user's explicit request.
Required Inputs
- Current active values for: project, role, phase, output_style, tone, and interaction_mode (if established).
- Open tasks or confirmed next steps from this session.
- Key decisions made during this session that affect future work.
- File paths actively referenced or modified this session.
Workflow
- Collect the current values for all required schema fields from active session state.
- List all open tasks — items in progress or confirmed next steps.
- List key decisions made this session that would affect future work.
- List file paths actively referenced or modified.
- Draft the checkpoint artifact using the schema in
references/checkpoint-schema.md. - Present the full draft to the user for review and approval before writing anything.
- Write the file only after the user explicitly approves.
- Suggest saving as
checkpoint-YYYY-MM-DD.mdin the project root or acheckpoints/folder if one exists. Let the user decide the exact path.
Output Expectations
- A Markdown file with YAML frontmatter containing all required schema fields.
- Human-readable summary paragraph below the frontmatter is optional but encouraged.
- The file must not be written without explicit user approval.
- Sensitive data (credentials, private client content) must never be included.
Resources
references/checkpoint-schema.mdfor field definitions, constraints, and an example artifact.
Constraints And Safety
- Checkpoint artifacts must be stored outside the instruction layer — never inside
AGENTS.mdor user context files. - Always require explicit user confirmation before writing the file.
- If a field value is unknown or not yet established, use
null. - Never include sensitive information such as credentials, API keys, or private client content.