justdoit
Skill0 starsChanged 4 months agoMITView on GitHub
Default execution-planning skill for almost any non-trivial repo task. Turn a raw task, feature request, PRD, or project brief into durable plan, status, and test-plan files, then hand back a concise ready-to-execute proposal.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- antoniolg/agent-kittheir own version, first seen Nov 8, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- antoniolg/agent-kit★ 100same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 10
Do not use when: the request is a trivial one-shot edit, pure discussion, or a factual answer with no execution surface.
- Distinctive: line 23
Every meaningful milestone has copy-pasteable validation commands and explicit done criteria.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
justdoit
Metadata
- Trigger when: the work is non-trivial enough to benefit from durable execution docs before or during implementation.
- Do not use when: the request is a trivial one-shot edit, pure discussion, or a factual answer with no execution surface.
Skill Purpose
Turn messy task input into a durable execution pack that another Codex run can resume from without reconstructing scope, sequencing, or validation from chat.
Instructions
- Determine the target files first. Prefer existing repo conventions; otherwise default to
docs/plans.md,docs/status.md, anddocs/test-plan.md. Normalize scope, constraints, risks, validation commands, and assumptions before drafting. - Build or update the plan, status, and test-plan files using the repo truth plus
~/.codex/skills/justdoit/references/plan-template.md,~/.codex/skills/justdoit/references/status-template.md, and~/.codex/skills/justdoit/references/test-plan-template.mdwhen you need the baseline structure. Keep milestones dependency-ordered and validation-first. - Finish with a short execution proposal that points to the written files, names what starts first, how validation will run, and what would stop the run. If the user only asked for planning, stop and wait for confirmation unless they already explicitly asked to execute immediately. If another skill is needed after planning, name it explicitly with a one-line reason.
Non-Negotiable Acceptance Criteria
- The plan is the source of truth; status and test-plan must line up with it.
- Every meaningful milestone has copy-pasteable validation commands and explicit done criteria.
- Assumptions are explicit instead of buried in prose.
- The skill does not paste huge file contents into chat unless the user explicitly asks for inspection.
Output
- A short product-level summary.
- The plan, status, and test-plan file paths.
- A compact
Ready to executehandoff plus either a confirmation question or a clear note that execution is already starting. Next skill options(only if needed):$agx-orchestrator— dispatch bounded execution through AGX;$parallel-worktrees— split substantial work into isolated lanes;$continuity-ledger— preserve cross-session state when the run will be long;$adversarial-review— run a skeptical second pass after implementation.
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
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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.

