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executing-plans

Use when you have a written implementation plan to execute inline in the current session with review checkpoints. Prefer subagent-driven-development when sub-agent dispatch is available.

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Executing Plans

Overview

Load plan, review critically, execute all tasks, report when complete.

Announce at start: "I'm using the executing-plans skill to implement this plan."

Note: This skill drives task-by-task execution inline in the current session. If your platform supports sub-agent dispatch (delegate_task, spawn_worker), the subagent-driven-development skill produces higher-quality results with two-stage review and isolated contexts. Use this skill when sub-agent dispatch is not available or your human partner explicitly chose inline execution.

The Process

Step 1: Load and Review Plan

  1. Read the plan file with read_file.
  2. Review critically — identify any questions or concerns about the plan.
  3. If concerns: raise them with your human partner before starting.
  4. If no concerns: create a todo per task and proceed.

Step 2: Execute Tasks

For each task:

  1. Mark the todo as in_progress.
  2. Follow each step exactly (the plan has bite-sized steps).
  3. Run verifications as specified — don't skip them.
  4. Mark the todo as completed only when the step's verification passes.

Step 3: Complete Development

After all tasks complete and verified:

  • Announce: "All plan tasks complete. Tests pass. Ready to wrap up."
  • Run any final-stage verification the plan demands (full test suite, lint, type checks).
  • Ask your human partner how they want to integrate the work (merge, PR, hand off).
  • Do not push, merge, or open a PR without explicit confirmation.

When to Stop and Ask for Help

STOP executing immediately when:

  • You hit a blocker (missing dependency, test fails, instruction unclear).
  • The plan has critical gaps preventing the next step.
  • You don't understand an instruction.
  • A verification fails repeatedly after the same fix attempt.

Ask for clarification rather than guessing.

When to Revisit Earlier Steps

Return to Review (Step 1) when:

  • Your human partner updates the plan based on your feedback.
  • The fundamental approach needs rethinking.

Don't force through blockers — stop and ask.

Remember

  • Review plan critically first.
  • Follow plan steps exactly.
  • Don't skip verifications.
  • Reference skills when the plan says to (use skill_view).
  • Stop when blocked — don't guess.
  • Never start implementation on the main/master branch without explicit consent.

Integration

Related skills:

  • writing-plans — Creates the plan this skill executes.
  • subagent-driven-development — Higher-quality alternative when sub-agent dispatch is available.
  • systematic-debugging — Use when a verification fails and the cause isn't obvious.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

The Arbor research-coordinator protocol: the OBSERVE -> IDEATE -> SELECT -> DISPATCH -> DECIDE cycle over a durable Idea Tree. Preloaded automatically on /auto-research sessions. The coordinator never edits code or runs commands — executors do that in isolated worktrees; the coordinator steers the tree with idea_tree / dispatch_experiments / merge_experiment.

日本語の概要は準備中です。原文の説明を表示しています。

invergent-ai/surogates282026年10月12日 更新

The Arbor executor workflow: clone the repo from the git bundle your brief hands you, implement and evaluate exactly ONE hypothesis with the file tools, then report structured results via worker_complete. Preloaded automatically on arbor-executor task workers. Never touch the held-out test split.

日本語の概要は準備中です。原文の説明を表示しています。

invergent-ai/surogates282026年10月12日 更新

Hard-gated ideation for an Arbor research run. Load at the START of every IDEATE round, before drafting any hypothesis. Enforces the PI mindset (mechanism over knob), the four-question first-principles probe, the kill-filter, and the four-line hypothesis format. Ported from Arbor's idea_drafting + first_principles_probe.

日本語の概要は準備中です。原文の説明を表示しています。

invergent-ai/surogates282026年10月12日 更新

DECIDE-phase doctrine for an Arbor research run: when to merge, prune, combine, or finalize; how the held-out merge gate works; and the rule that the final report uses TEST scores. Load before deciding what to do with completed experiments.

日本語の概要は準備中です。原文の説明を表示しています。

invergent-ai/surogates282026年10月12日 更新

Intake for an autonomous research run (Arbor). Use when the user wants to optimize a metric in a repo over many isolated experiments — 'optimize this benchmark', 'improve the model F1 overnight', 'beat the leaderboard'. Discovers the repo/eval/splits, measures the baseline, confirms a Research Contract, then emits a ready-to-send /auto-research command. Does NOT start the run itself.

日本語の概要は準備中です。原文の説明を表示しています。

invergent-ai/surogates282026年10月12日 更新

You MUST use this before any creative work — creating features, building components, drafting documents, designing workflows, or modifying behavior. Explores your human partner's intent, requirements, and design before any implementation begins.

日本語の概要は準備中です。原文の説明を表示しています。

invergent-ai/surogates282026年10月12日 更新

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