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About
Use cases: testing, ml, agent-building
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What's inside
- Skill name
bmad-checkpoint-preview- Description
- LLM-assisted human-in-the-loop review. Make sense of a change, focus attention where it matters, test. Use when the user says "checkpoint", "human review", or "walk me through this change".
- License
- MIT
- Instructions
- 65 lines in SKILL.md · view on GitHub
Files (8)
- SKILL.md
- customize.toml
- generate-trail.md
- step-01-orientation.md
- step-02-walkthrough.md
- step-03-detail-pass.md
- step-04-testing.md
- step-05-wrapup.md
SKILL.md (first lines)
# Checkpoint Review Workflow
**Goal:** Guide a human through reviewing a change — from purpose and context into details.
**Your Role:** You are assisting the user in reviewing a change.
## Conventions
- Bare paths (e.g. `step-01-orientation.md`) resolve from the skill root.
- `{skill-root}` resolves to this skill's installed directory (where `customize.toml` lives).
- `{project-root}`-prefixed paths resolve from the project working directory.
- `{skill-name}` resolves to the skill directory's basename.
## On Activation
### Step 1: Resolve the Workflow Block
Run: `python3 {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow`
**If the script fails**, resolve the `workflow` block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:
1. `{skill-root}/customize.toml` — defaults
2. `{project-root}/_bmad/custom/{skill-name}.toml` — team overrides
3. `{project-root}/_bmad/custom/{skill-name}.user.toml` — personal overrides
Any missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by `code` or `id` replace matching entries and append new entries, and all other arrays append.
### Step 2: Execute Prepend Steps
Execute each entry in `{workflow.activation_steps_prepend}` in order before proceeding.
### Step 3: Load Persistent Facts
Treat every entry in `{workflow.persistent_facts}` as foundational context you carry for the rest of the workflow run. Entries prefixed `file:` are paths or globs under `{project-root}` — load the referenced contents as facts. All other entries are facts verbatim.
### Step 4: Load Config
Load config from `{project-root}/_bmad/bmm/config.yaml` and resolve:
- `implementation_artifacts`
- `planning_artifacts`
- `communication_language`
- `document_output_language`
### Step 5: Greet the User
Greet the user, speaking in `{communication_language}`.
### Step 6: Execute Append Steps
Execute each entry in `{workflow.activation_steps_append}` in order.
Activation is complete. If `activation_steps_prepend` or `activation_steps_append` were non-empty, confirm every entry was executed in order before proceeding. Do not begin the main workflow until all activation steps have been completed.
## Global Step Rules (apply to every step)
- **Path:line format** — Every code reference must use CWD-relative `path:line` format (no leading `/`) so it is clickable in IDE-embedded terminals (e.g., `src/auth/middleware.ts:42`).
- **Front-load then shut up** — Present the entire output for the current step in a single coherent message. Do not ask questions mid-step, do not drip-feed, do not pause between sections.
- **Language** — Speak in `{communication_language}`. Write any file output in `{document_output_language}`.
## FIRST STEP
Read fully and follow `./step-01-orientation.md` to begin.From azharameen/group-run, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 18
- Last commit (this folder)
- Jul 31, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/azharameen/group-run
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
bmad-checkpoint-preview skill. Agent Mart. https://agentmart.dev/skills/azharameen-bmad-checkpoint-preview (last updated 2026-10-24)