accountable-engineerin…
Use explicit human checkpoints for architecture, security, rollout, or operational decisions.
Resume work from previous handoff sessions stored in .planning/handoffs/
$ npx -y skills add jellydn/my-ai-tools --skill pickup --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/pickupContext preview
The summary Claude sees to decide when to auto-load this skill.
Resume work from previous handoff sessions stored in .planning/handoffs/
name: pickup description: "Resume work from previous handoff sessions stored in .planning/handoffs/" license: MIT compatibility: cline, claude, opencode, amp, codex, gemini, cursor, pi hint: Use when resuming work from a previous handoff session user-invocable: true disable-model-invocation: true metadata: audience: all workflow: workflow
Resumes work from previous handoff sessions which are stored in `.planning/handoffs/`.
`/pickup [HANDOFF_FILE]`
If no handoff file is specified, will show available handoffs and prompt for selection.
1. Find available handoffs in `.planning/handoffs/` 2. Read the selected handoff file 3. Present the handoff summary to the user 4. Ask the user to confirm they want to continue 5. If confirmed, proceed with the next step described in the handoff
To see available handoffs:
ls -la .planning/handoffs/
Handoffs are named in format: `[YYYY-MM-DD]-[slug].md`
Portable, source-controlled configuration for AI coding assistants. my-ai-tools installs one consistent set of agent guidelines, skills, commands, hooks, MCP servers, and tool settings across supported AI coding assistants.
Use explicit human checkpoints for architecture, security, rollout, or operational decisions.
Record architecture decisions with ADRs — captures why, alternatives considered, and consequences
Use when monitoring an open GitHub PR for CI failures, review feedback, mergeability, and safe retries or fixes.
Inspect history and architecture for hidden constraints before risky cross-cutting changes.
Build an interactive report or experiment when the user asks to explore model capabilities.
Audit a diff for structural maintainability and unnecessary complexity.