agentleFS
rakaadirakaadi/agent-kit/skills/execute-plan/SKILL.md

execute-plan

Skill1 starsChanged 3 months agoMITView on GitHub

Execute or resume an attached or referenced implementation plan through repository inspection, implementation, verification, and complete-plan review. Use for full or partial plan execution, including free-form instructions to select phases or task IDs, skip work, delegate a task independently, reserve checks for a human, or impose task-specific constraints.

25 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use create-plan, to-spec and 6 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • JetBrainsSkill

    create-plan

    Research the codebase and create an implementation plan with architecture notes, design document, and track decomposition. Use when starting a new feature or large change.

    Also in 4 projects that use this

  • GoogleSkill

    to-spec

    Turn the current conversation into a spec and publish it to the project issue tracker — no interview, just synthesis of what you've already discussed.

    Also in 3 projects that use this

  • MicrosoftSkill

    grill-with-docs

    Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.

    Also in 4 projects that use this

  • GoogleSkill

    grill-me

    A relentless interview to sharpen a plan or design.

    Also in 6 projects that use this

  • NVIDIASkill

    research

    Before designing a feature, research how comparable libraries solve the problem, check best practices, known pitfalls, and upstream changes. Use when starting a new feature, investigating an unfamiliar area, or the user asks to research something.

    Also in 4 projects that use this

  • Hugging FaceSkill

    implement

    Make tests pass. Invoke after /write-tests produces failing tests.

    Also in 3 projects that use this

  • +2 more from google

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 8 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 23 edited versions we read keep these.

  • 8

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If the plan and repository differ, make the smallest evidence-based adaptation and record the affected task IDs.

    line 17
  2. Distinctive:

    Before implementation, build a run manifest containing:

    line 21
  3. Distinctive:

    every plan task's scope state, dependencies, acceptance criteria, and verification requirements.

    line 24
  4. Distinctive:

    every planned Human Review Focus.

    line 25
  5. Distinctive:

    Use these task states:

    line 29
  6. Distinctive:

    Treat plan commit boundaries as checkpoints.

    line 51
  7. Distinctive:

    Run task-level verification at its boundary and applicable final verification afterward.

    line 52
  8. Very specific:

    Run this gate only after every task in the complete plan is Completed.

    line 64
  9. Distinctive:

    Update progress only when the plan is a maintained, writable execution artifact:

    line 80

“Common” is measured: kept by at least 6 in 10 of the 23 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Execute Plan

Implement the plan against the current repository, using the user's prompt to define this run's scope.

Execution Contract

Use the entire user prompt as the runtime override layer. It may select the full plan, phases, or task IDs; skip or defer work; assign tasks to subagents; reserve checks for a human; change sequencing; add task-specific constraints; or set a stopping point. Apply these overrides before execution and report their effects.

Read the complete prompt, repository instructions, and plan before editing. Treat every plan section as input, including file structure, dependencies, required skills, acceptance criteria, Human Review Focuses, verification, progress state, out-of-scope boundaries, global decisions, and checkpoints. For HTML plans, read the visible semantic content and preserve presentation code when updating the artifact.

If the plan and repository differ, make the smallest evidence-based adaptation and record the affected task IDs. Ask only when a material choice cannot be inferred safely.

Run Manifest

Before implementation, build a run manifest containing:

  • the target repository and run baseline;
  • every plan task's scope state, dependencies, acceptance criteria, and verification requirements;
  • every planned Human Review Focus;
  • existing or previously completed work;
  • task ownership by the main agent, a subagent, or a human.

Use these task states:

  • Selected: included in this run.
  • Completed: acceptance criteria are satisfied with permitted verification evidence.
  • Skipped: the user explicitly excluded the task.
  • Deferred: the task remains planned but is outside this partial run or stopping point.
  • Blocked: a selected task cannot proceed because of an unmet dependency, missing input, unavailable required capability, or authority boundary.

Preflight completes when every plan task is selected, skipped, deferred, already completed, or blocked.

Program Design Gate

Before implementing a selected task that introduces or substantially reshapes modules, interfaces, types, file layout, dependencies, or control flow, use the program-design skill and obtain explicit approval of the proposed code shape. Group tasks behind one proposal when they share the same design. Small fixes, local implementation changes, and mechanical edits do not require this gate.

Approval of the implementation plan does not satisfy this gate unless the plan already contains an explicitly approved program design that still matches the current repository. If implementation evidence later forces a material deviation, return to program-design with the affected delta before continuing.

Implement And Verify

Execute selected tasks in dependency order while preserving plan boundaries and intermediate working-state requirements.

  • Assign disjoint file ownership to concurrent tasks.
  • Load skills and references required by a task before starting it.
  • Treat plan commit boundaries as checkpoints. Create commits only when the user or plan explicitly requires them.
  • Run task-level verification at its boundary and applicable final verification afterward.

Apply task ownership from the user prompt before ownership stated in the plan. For delegated work, follow the subagent-dispatch skill, provide self-contained task context, and assign non-overlapping file ownership. The main agent integrates the result and verifies its acceptance criteria. If explicitly required delegation is unavailable, mark the task blocked or request direction instead of silently executing it in the main context.

For a human-owned check, prepare the test or verification artifact and report Not run, the ownership reason, and the exact command or manual steps. Keep its result unverified until human evidence exists. When the environment blocks a check, run the next applicable non-destructive check and report the remaining validation gap.

After implementing each selected task, reassess its Human Review Focus against the actual implementation. Keep at most three items and name the narrowest stable file, symbol, screen, workflow, policy, or boundary; the judgment the human should apply; and why agent or automated validation is insufficient. Narrow or add a focus when implementation evidence warrants it. Remove one only when the implementation eliminates the need for that judgment, and record the reason. Update the task in a maintained, writable plan so it shows only the current focus.

A Human Review Focus is an advisory review map. It never becomes a dependency, acceptance criterion, verification result, human-owned check, task state, review gate, or completion gate. Agent reviews do not substitute for the named human judgment, and a human review does not clear or complete the focus. Report findings from any performed human review through the ordinary implementation workflow.

Complete-Plan Review Gate

Run this gate only after every task in the complete plan is Completed. Completing every task selected for a partial run does not satisfy this gate. For a partial run, update plan progress and report the review gate as Not run because the plan remains incomplete.

At the final gate, use the review-implementation skill with a self-contained implementation packet:

  • the complete plan path and final user overrides;
  • the full-plan baseline and current diff or commit range covering every task;
  • human-owned checks and their current evidence;
  • verification evidence and justified deviations.
  • explicit task-scoped authorization for Architectural Review, when granted.

The review skill owns reviewer isolation, finding validation, remediation, targeted revalidation, blind rereview, cycle accounting, and escalation. Consume its terminal result as Passed, Blocked, or Awaiting architectural-review decision. A missing required reviewer or review gate cannot produce Passed.

Complete The Run

Recheck every selected task's acceptance criteria against the implementation and fresh verification evidence.

Update progress only when the plan is a maintained, writable execution artifact:

  • Current status: Completed only when every plan task is completed; Blocked when selected work cannot proceed; otherwise In progress.
  • Started on: set when the first task begins.
  • Completed on: set only with overall Completed.
  • Last executed tasks: record executed task IDs newest first.
  • Current blocker or next focus: record the blocker or next dependency-ready task.
  • Unplanned necessary work: record required work outside the original task list.

Preserve archival plans unchanged and represent partial completion without marking the overall plan completed.

Report concisely:

  • completed, skipped, deferred, or blocked task IDs;
  • changed files and behavior;
  • verification with Passed, Failed, or Not run status;
  • plan deviations;
  • spec-compliance, code-quality, and authorized architectural findings addressed;
  • Human Review Focuses grouped by task, including focuses a human already reviewed;
  • Human Review Focus Changes with the task ID and reason, only when planned focuses changed;
  • remaining human checks, blockers, or follow-up work.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.