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Executing Plans

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LayneChai
executing-plans

Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available

Overview

PublisherLayneChai
Repositorysuperpowers-dsh
Skill nameexecuting-plans
Stars
130
Forks
10
Bundled files
2
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by LayneChai on GitHub. Read the source before you install it.

Installation

Install the Executing Plans AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/LayneChai/superpowers-dsh/tree/main/skills/executing-plans
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LayneChai/superpowers-dsh.git /tmp/superpowers-dsh
mkdir -p .claude/skills
cp -r /tmp/superpowers-dsh/skills/executing-plans .claude/skills/executing-plans
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Executing Plans in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Executing Plans on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Executing Plans is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Executing Plans

Execute the plan yourself, task by task, in this session: no implementer subagent per task, no reviewer per task. One fresh-context review of the whole branch at the end.

Why inline: Subagent-driven development pays for a fresh implementer and a fresh reviewer on every task, each re-reading the codebase from zero. Inline execution pays for one context (yours) plus one reviewer at the end. What it gives up is a fresh context per task and a second pair of eyes per task. This skill keeps what those two things bought, by other means: the brief is the spec, the ledger is your memory, TDD is the per-task gate, and the final reviewer is the second pair of eyes.

Core principle: The plan already did the thinking. Execute it exactly, prove each step with a test you watched fail and then pass, and leave a record that survives your own forgetting.

Narration: between tool calls, narrate at most one short line — the ledger and the tool results carry the record.

Continuous execution: Do not pause to check in with your human partner between tasks. They chose inline execution to spend less, not to answer "should I continue?" after every task. Execute all tasks from the plan without stopping.

Rulings, not stalls. Conflicts, ambiguities, plan defects — decide them. The spec is the binding authority, the plan is its argument, and your judgment settles what neither answers. Record every decision in the ledger as Ruling: <what you decided> — <why> — <what it costs if wrong>, and keep going. Deviating from the plan without a ledgered ruling is a decision made in secret.

Four things stop you, and only these: an irreversible or destructive operation; a security-sensitive action; a side effect outside this worktree that norms say you ask about first (a merge, a push to a shared branch, a publish); and a plan so broken that every path forward is a guess. For those, stop and ask.

When to Use

  • You have a plan from writing-plans and your human partner chose inline (Native) execution at the handoff.
  • No subagent tool is available in this session, or your human partner chose Native. On the DeepSeek Harness subagent / subagent_fork normally ARE available (see ../using-superpowers/references/dsh-tools.md), so prefer subagent-driven-development; run the plan here when the work must stay in one context. Never fabricate a dispatch.
  • Tasks are mostly independent — the same precondition as subagent-driven-development.

A fully specified plan makes inline execution transcription plus testing: it runs well on a mid-tier session model, and the one place the most capable model earns its cost is the final review, which this skill dispatches separately. Tell your human partner so when they choose inline.

Prefer subagent-driven-development when your human partner wants a review gate on every task, or when the plan is long enough that its later tasks would run on a compacted context. Inline execution over a long plan still works — the ledger is what makes it recoverable — but the last tasks get the least of you.

The Process

dot
digraph process {
    rankdir=TB;

    subgraph cluster_per_task {
        label="Per Task";
        "task-start: brief + BASE; read the brief" [shape=box];
        "Work the steps in order: TDD, run every verification, read every output" [shape=box];
        "Step output matches plan's Expected?" [shape=diamond];
        "Plan wrong? Rule and ledger. Code wrong? systematic-debugging" [shape=box];
        "Commit as the plan's commit steps say" [shape=box];
        "Completion contract met?" [shape=diamond];
        "task-done: run tests, ledger the result; mark todo complete" [shape=box];
    }

    "Setup: worktree, workspace + ledger, read plan + spec, pre-flight scan" [shape=box];
    "More tasks remain?" [shape=diamond];
    "Final whole-branch review (fresh reviewer if you have one)" [shape=box];
    "Re-grade, then: Critical/Important → ONE fix pass, each fix RED→GREEN + green suite; Minor → ledger" [shape=box];
    "Final review clean: delete this plan's workspace" [shape=box];
    "Use finishing-a-development-branch" [shape=box style=filled fillcolor=lightgreen];

    "Setup: worktree, workspace + ledger, read plan + spec, pre-flight scan" -> "task-start: brief + BASE; read the brief";
    "task-start: brief + BASE; read the brief" -> "Work the steps in order: TDD, run every verification, read every output";
    "Work the steps in order: TDD, run every verification, read every output" -> "Step output matches plan's Expected?";
    "Step output matches plan's Expected?" -> "Plan wrong? Rule and ledger. Code wrong? systematic-debugging" [label="no"];
    "Plan wrong? Rule and ledger. Code wrong? systematic-debugging" -> "Work the steps in order: TDD, run every verification, read every output";
    "Step output matches plan's Expected?" -> "Commit as the plan's commit steps say" [label="yes, last step"];
    "Commit as the plan's commit steps say" -> "Completion contract met?";
    "Completion contract met?" -> "Work the steps in order: TDD, run every verification, read every output" [label="no - finish the task"];
    "Completion contract met?" -> "task-done: run tests, ledger the result; mark todo complete" [label="yes"];
    "task-done: run tests, ledger the result; mark todo complete" -> "More tasks remain?";
    "More tasks remain?" -> "task-start: brief + BASE; read the brief" [label="yes"];
    "More tasks remain?" -> "Final whole-branch review (fresh reviewer if you have one)" [label="no"];
    "Final whole-branch review (fresh reviewer if you have one)" -> "Re-grade, then: Critical/Important → ONE fix pass, each fix RED→GREEN + green suite; Minor → ledger";
    "Re-grade, then: Critical/Important → ONE fix pass, each fix RED→GREEN + green suite; Minor → ledger" -> "Final review clean: delete this plan's workspace";
    "Final review clean: delete this plan's workspace" -> "Use finishing-a-development-branch";
}

Setup

Ensure the work happens in an isolated workspace: use using-git-worktrees to create one or verify the existing one. Never start implementation on a main/master branch without your human partner's explicit consent.

Conversation memory does not survive compaction. An inline executor that loses its place re-implements tasks whose commits already exist — the same failure as a controller re-dispatching them, paid for in your own context. Track progress in a ledger file, not only in todos. Harness todos are a live view; the ledger is the record.

The workspace and ledger are shared with subagent-driven-development — same directory, same format — so a plan can change executors mid-flight and the new one resumes from the same ledger.

  • Each plan owns a workspace: at skill start, run bash ../subagent-driven-development/scripts/sdd-workspace PLAN_FILE — it prints the plan's git-ignored directory (<repo-root>/.superpowers/sdd/<plan-basename>/), home to every artifact for THIS plan: ledger, briefs, review packages. Another plan's directory is never yours to read or write.
  • Check for this plan's ledger at <workspace>/progress.md. If its first line names your plan file, tasks with a Task <N>: complete line are DONE — do not redo them; resume at the first task without one. Their commits exist in git even when your context no longer remembers making them: after compaction, trust the ledger and git log over your own recollection. A ledger whose first line names a different plan file is another plan's progress: leave it and start your own, fresh.
  • Create the ledger with its identity as the first line: # SDD ledger — plan: <plan file path>.
  • git clean -fdx will destroy the workspace (it's git-ignored scratch); if that happens, recover from git log.

Read the plan once, note its context and Global Constraints, and create a todo per task. If the plan names a Spec, read that too: the spec is the authority the plan argues from, and conflicts inside the plan resolve against it. A plan with no reachable spec gets a ledger note saying so — rulings made without one are provisional.

REQUIRED SUB-SKILL: load test-driven-development now, before Task 1. It governs every step of every task below; a plan whose steps already say "write the failing test first" does not exempt you from reading it.

Before Task 1, scan the plan for conflicts between tasks. The plan's Interfaces blocks tell you where to look: for every task that consumes what an earlier task produces, one ledger row — the two tasks, what one produces against what the other consumes, and what you found. Tasks that share nothing get no row; a plan whose tasks share nothing gets the single line Pre-flight: no shared interfaces. Rule on each conflict a row surfaces with the spec as the binding authority, record the ruling beside its row, and start Task 1. Each task's own text is checked when you read its brief, not here.

The Task Loop

Everything you print, and every tool result, stays resident in your context for the rest of the session. Redirect long test output to a file in the workspace and read its tail; read a brief, not the whole plan.

1. Take the task

  • Run this skill's bash scripts/task-start PLAN_FILE N. It prints the brief path and BASE (the commit the task's range is cut from) in one call. Read the brief for every task, including ones you remember from setup: what you remember is a summary, the brief has the exact values, signatures, and test cases.
  • Mark the task's todo in_progress.

Every tool call is a turn that re-reads your whole context. Bookkeeping rides along with work — a ledger append in the same call as the commit, never in a call of its own.

2. Work the steps

The plan's steps are already in RED-GREEN order; follow them in that order under test-driven-development, loaded at setup. A test step's code is written first and run first. Watching it fail is a step, not a formality — a test that passes before the implementation exists is a finding about the test.

Every step that runs a command has an Expected: line. Run the command, read its output, and compare. Three outcomes:

  • Matches. Next step.
  • The code is wrong. Use systematic-debugging. Find the cause; never patch the symptom to make the step's output match.
  • The plan is wrong — a step contradicts the spec, an interface from an earlier task doesn't match what this task consumes, a command that cannot work. Rule on the smallest change that satisfies the spec, ledger it as Task <N>: Ruling: <finding> — <what you decided and why>, and continue. The ruling is carried, not remembered: later tasks that touch the same interface read it from the ledger.

Commit as the plan's commit steps say. A task that spans several commits is fine; BASE is what the review range is cut from, never HEAD~1.

3. The completion contract

Before a task's ledger line, all of the following are true, with evidence in this session — not inferred from the diff looking right:

  • Every test the brief names exists and ran in this task, and you read the output.
  • The final test run for the task passed — task-done is that run, and it writes the command and result into the ledger line.
  • Every Expected: line in the brief was compared against real output.
  • Every deviation from the brief has a Ruling: line in the ledger.

REQUIRED SUB-SKILL: verification-before-completion governs the claim. If any item is missing, the task is not complete: finish it.

4. Complete the task

Run this skill's bash scripts/task-done PLAN_FILE N BASE -- <test command> with the test command the brief names for the whole task. It runs the tests, keeps the full output in the workspace, prints the tail, and — only if they pass — appends the completion line to the ledger:

Task <N>: complete (commits <base7>..<head7>, tests: <command> → <result>)

A failing run records nothing; the task is not complete. When it records, mark the todo complete and take the next task.

Final Review

Run bash ../subagent-driven-development/scripts/review-package PLAN_FILE MERGE_BASE HEAD (MERGE_BASE = the commit the branch started from, e.g. git merge-base main HEAD) and review from the file it prints.

With a subagent tool: dispatch the reviewer on the most capable available model — the whole-branch review is a judgment task — using requesting-code-review's code-reviewer.md, with the package path, the plan and spec paths, the plan's Review Focus section verbatim if it has one (the input classes and failure modes the plan's tests do not exercise — the reviewer checks each deliberately), and a pointer to the ledger's Ruling: lines so it can weigh the calls you made. Specify the model explicitly; an omitted model inherits the session's, which may not be the most capable. This is the one fresh context the whole run buys. Do not skip it, and do not replace it with your own read of the diff.

Without a subagent tool: read code-reviewer.md and perform that review yourself against the package, as a separate pass after the last task's ledger line. Write Final review: self-review (no subagent tool) to the ledger, and say so in your final message: a self-review by the author is weaker than a fresh reviewer, and your human partner decides whether that is enough before merge.

Sort the findings before you act on any of them. The reviewer's severity labels are advice; the gate is yours. Its "Declined to judge" list is yours too: every line there is a ruling you make and ledger, exactly like a plan conflict — Final: Ruling: <behavior the reviewer set aside> — <what a reasonable person using this software gets, and why that stands or why it is now a finding> — <cost if wrong>. Re-grade first, by effect: the spec is a vision document, and a finding's grade is what a reasonable person using this software gets if it ships, not whether the spec names the input that triggers it — a reviewer who set a finding at Minor because the spec was silent has graded the spec, not the effect. Then:

  • Critical and Important enter the fix pass.
  • Minor goes to the ledger as Final: minor (deferred): <one-liner> and to your final message under "Deferred minors". Minors never enter the fix pass, and never become rulings — a ruling is a decision about a conflict, not a note that you declined a polish suggestion.

Fix the Critical and Important findings yourself — you are the implementer here — in ONE pass. Each fix is verified by TDD, not by a second reviewer: write the test that reproduces the finding, watch it fail, make it pass, then run the whole suite. Record each in the ledger as Final: fixed <finding> — <test name> RED→GREEN, suite <N>/<N>. A fix without a test that failed first is not verified; a suite that is not green after the pass means the pass is not over. Do not dispatch a re-review: it would re-read a diff whose covering tests already answer "addressed" and whose suite run already answers "broke nothing".

A finding you decide not to fix is a ruling — Final: Ruling: <finding> — <why the code stands> — <cost if wrong> — and reaches your human partner in the rulings list. There is no second fix pass.

Finish

Before you delete anything, collect every ledger line containing Ruling: into your final message under "Rulings I made", in the order you made them, each with what it costs if wrong, and every minor (deferred) line under "Deferred minors". Both lists are exhaustive. Your final message is the only place the decisions you took on your human partner's behalf — and the findings you chose not to act on — reach them.

When the final review is clean and its fixes are committed, delete this plan's workspace directory — the git history is the record now. Sibling directories belong to other plans; leave them alone.

Use finishing-a-development-branch.

Common Rationalizations

ExcuseReality
"I remember what Task N says"You remember a summary. The brief has the exact values. Read it.
"The plan's code is right, skip watching the test fail"A test you never saw fail proves nothing. It is one step. Run it.
"I'll run the full suite at the end instead of per step"Per-step runs are how you learn which step broke it. The end-of-task run is the contract, not a substitute.
"The plan is wrong here, I'll just do the right thing"Do the right thing and ledger the ruling. Unledgered deviation is a decision made in secret.
"I'll write the ledger lines after a few tasks"Compaction does not wait for a convenient moment. One line per task, in the same message as the commit.
"Let me check in before the next task"They chose inline to spend less. Progress prompts spend their time instead. Only the four stops stop you.
"I read my own diff carefully; the final reviewer is redundant"Same author, same blind spots. The reviewer is the only fresh context this run buys.
"Tests should pass, the change was trivial""Should" is not evidence. The contract requires the command and its output.
"Subagents are slow and expensive, I'll skip the final review too"Inline already removed the per-task reviewers. One review of the whole branch is the floor, not the ceiling.
"The reviewer said Minor, so it's Minor"The label graded the spec's silence. Grade what the person gets. Re-grade, then gate.
"The fix is obvious, no need for a failing test first"The failing test is the only proof the finding was real and is now gone. Without it you have a diff and a hope.
"I'll fix the minors too while I'm in there"Every minor you fix is a test, a fix, and a suite run your partner did not ask for. Ledger them; your partner decides.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Executing Plans AI skill do?

Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available

Why use Executing Plans on TypingMind?

Because you install it once and use it with any model. Executing Plans is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Executing Plans in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LayneChai/superpowers-dsh/tree/main/skills/executing-plans. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Executing Plans?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Executing Plans?

As many as you like. As long as a model supports skills, you can use Executing Plans with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Executing Plans AI skill free?

It is published on GitHub by LayneChai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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