executing-plans skill
Executes written plans through batch execution with human checkpoints, progress tracking, and automatic rollback capabilities.
- GitHub stars
- 44
- Files
- 1
- Last commit
- Apr 12, 2026
- License
- MIT
- Allowed tools
- —
What does the executing-plans skill do?
executing-plans executes written plans through batch execution with human checkpoints, progress tracking, and automatic rollback capabilities.
Summary generated from the skill's SKILL.md.
About the executing-plans skill
Driving a written plan through batch execution with human oversight is what this skill enables for developers managing complex, multi-step tasks. When an agent loads this skill, it follows a step-by-step sequence, verifying the success of each action before moving forward. It is designed for scenarios where changes carry risk, such as applying multi-file modifications in a specific order or performing destructive operations like migrations and deploys.
The engine maintains a state machine to track whether steps are pending, in-progress, verified, failed, or rolled-back. It provides transparency by reporting completion percentages, elapsed time, and remaining estimates. To ensure safety, the system records the pre-change state of affected files before every modification. If a verification command fails, the agent can automatically revert to the last known-good checkpoint or present the human operator with options to retry, modify, skip, or abort the process.
What an agent can do with it
- 1Execute multi-file code changesApply a series of complex file modifications in a specific, required order.
- 2Manage high-risk operationsPerform destructive tasks like database migrations or deployments with built-in safety nets.
- 3Monitor long-running task progressTrack the percentage of completion and estimated time remaining during a batch process.
- 4Recover from failed execution stepsAutomatically revert files to their previous state if a verification command does not pass.
Written from the skill's SKILL.md. Every use case is checked against a quote from it.
How to install the executing-plans skill
Each command copies the skill folder into the client's skills directory. Restart the client or start a new session to load it.Install the executing-plans skill in Plugin
/plugin marketplace add itallstartedwithaidea/agent-skills /plugin install software-dev-skills@googleadsagent-skills
Install the executing-plans skill in Claude Code
~/.claude/skills/executing-plans/SKILL.md
$ npx degit itallstartedwithaidea/agent-skills/skills/software-dev/executing-plans ~/.claude/skills/executing-plansInstall the executing-plans skill in Claude Code (project)
.claude/skills/executing-plans/SKILL.md
$ npx degit itallstartedwithaidea/agent-skills/skills/software-dev/executing-plans .claude/skills/executing-plansInstall the executing-plans skill in Codex
~/.agents/skills/executing-plans/SKILL.md
$ npx degit itallstartedwithaidea/agent-skills/skills/software-dev/executing-plans ~/.agents/skills/executing-plansInstall the executing-plans skill in Gemini CLI
~/.gemini/skills/executing-plans/SKILL.md
$ npx degit itallstartedwithaidea/agent-skills/skills/software-dev/executing-plans ~/.gemini/skills/executing-plansInstall the executing-plans skill in Claude.ai
npx degit itallstartedwithaidea/agent-skills/skills/software-dev/executing-plans executing-plans && zip -r executing-plans.zip executing-plans # claude.ai → Customize → Skills → + → Create skill → Upload a skill → executing-plans.zip
SKILL.md
View on GitHubExecuting Plans
Part of Agent Skills™ by googleadsagent.ai™
Description
Executing Plans takes a written plan and drives it through batch execution with human checkpoints, progress tracking, and rollback capability. The agent follows the plan step by step, verifying each step's success before proceeding, pausing at designated checkpoints for human confirmation, and maintaining the ability to reverse any step that fails.
Plans without disciplined execution degrade into wishful thinking. This skill enforces the contract: every step runs in order, every verification command must pass, and any failure halts forward progress until resolved. The agent tracks completion percentage, elapsed time, and remaining estimates, giving the human operator clear visibility into progress.
Rollback capability is built into the execution model. Before applying each step, the agent records the pre-change state. If a step fails verification, the agent can revert to the last known-good checkpoint automatically or present the human with options: retry, skip, modify, or abort.
Use When
- A written plan exists and is approved for execution
- Multi-file changes must be applied in a specific order
- The user wants oversight at key decision points during execution
- Changes carry risk and need rollback capability
- Execution spans multiple sessions or agents
- Progress tracking is needed for transparency
How It Works
graph TD
A[Load Plan] --> B[Step N]
B --> C[Record Pre-Change State]
C --> D[Apply Change]
D --> E[Run Verification]
E --> F{Verification Passes?}
F -->|Yes| G{Checkpoint Step?}
G -->|Yes| H[Pause for Human Review]
G -->|No| I[Update Progress]
H --> I
I --> J{More Steps?}
J -->|Yes| B
J -->|No| K[Execution Complete]
F -->|No| L{Rollback?}
L -->|Auto| M[Revert to Last Checkpoint]
L -->|Manual| N[Present Options to Human]
M --> B
The execution engine maintains a state machine for each step: pending, in-progress, verified, failed, rolled-back. Human checkpoints are configurable—the default places them after every 3 steps and before any destructive operation.
Implementation
class PlanExecutor:
def __init__(self, plan, checkpoint_interval=3):
self.plan = plan
self.checkpoint_interval = checkpoint_interval
self.snapshots = {}
self.progress = []
def execute(self):
for i, step in enumerate(self.plan.steps):
self.snapshots[i] = self.capture_state(step.affected_files)
self.update_status(step, "in_progress")
try:
self.apply_change(step)
result = self.run_verification(step.verify_command)
if not result.success:
raise VerificationError(step, result.output)
self.update_status(step, "verified")
self.report_progress(i + 1, len(self.plan.steps))
if self.is_checkpoint(i):
self.pause_for_human_review(step)
except (ApplyError, VerificationError) as e:
self.update_status(step, "failed")
self.handle_failure(i, e)
def handle_failure(self, step_index, error):
self.rollback_to(step_index)
options = [
"retry: Re-attempt this step",
"modify: Edit the step and retry",
"skip: Mark as skipped and continue",
"abort: Stop execution entirely",
]
return self.prompt_human(error, options)
def rollback_to(self, step_index):
for path, content in self.snapshots[step_index].items():
self.restore_file(path, content)
def report_progress(self, completed, total):
pct = (completed / total) * 100
print(f"Progress: {completed}/{total} ({pct:.0f}%) | "
f"Elapsed: {self.elapsed()} | "
f"Remaining: ~{self.estimate_remaining(completed, total)}")
Best Practices
- Always verify plan approval before starting execution
- Capture file state before every modification for rollback safety
- Place checkpoints before destructive operations (deletes, migrations, deploys)
- Report progress after each step, not just at the end
- If a step fails twice, escalate to the human rather than retrying indefinitely
- Commit after each verified step to create restore points in version control
Platform Compatibility
| Platform | Support | Notes |
|---|---|---|
| Cursor | Full | Shell + TodoWrite for progress |
| VS Code | Full | Terminal-based execution |
| Windsurf | Full | Cascade step execution |
| Claude Code | Full | Shell + checkpoint prompts |
| Cline | Full | Task runner integration |
| aider | Partial | No native checkpoint support |
Related Skills
- Writing Plans - Plan authoring that produces the step-by-step specifications this skill executes
- Subagent-Driven Development - Parallel task dispatch that delegates plan steps to isolated subagents
- Git Worktrees - Isolated workspaces that provide clean baselines for verifying each execution step
Keywords
plan-execution batch-execution human-checkpoints rollback progress-tracking verification state-machine step-by-step-execution
© 2026 googleadsagent.ai™ | Agent Skills™ | MIT License
Files in this skill
1executing-plans skill questions
How do I install the executing-plans skill in Claude Code?
Run npx degit itallstartedwithaidea/agent-skills/skills/software-dev/executing-plans ~/.claude/skills/executing-plans. Claude Code loads skills from ~/.claude/skills (all projects) or .claude/skills (one project) and uses a skill when its description matches the task.
Which clients can use the executing-plans skill?
Any client that reads the Agent Skills format: Claude Code, Codex, Gemini CLI and claude.ai (upload as a ZIP). Scripts in the skill run only where the client allows code execution.
How does the skill handle failures during execution?
The agent can automatically revert to the last known-good checkpoint or present the human operator with options to retry, skip, modify, or abort.
Where are human checkpoints placed by default?
By default, checkpoints are placed after every three steps and before any operation that is considered destructive.
What information is provided during progress tracking?
The agent tracks the completion percentage, elapsed time, and estimated remaining time to provide visibility.