القائمة
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.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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.
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.
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.
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.
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.
Pitfalls, examples, and edge cases for workers executing a Surogates subagent task. Loaded automatically when the dispatcher spawns a session bound to a Task (Session.task_id is set).
| name | executing-plans |
| description | 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. |
| version | 1.0.0 |
| author | Surogate Agent (adapted from obra/superpowers) |
| license | MIT |
| tags | ["process","implementation","execution"] |
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.
read_file.todo per task and proceed.For each task:
todo as in_progress.todo as completed only when the step's verification passes.After all tasks complete and verified:
STOP executing immediately when:
Ask for clarification rather than guessing.
Return to Review (Step 1) when:
Don't force through blockers — stop and ask.
skill_view).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.