autoplan

autoplan is a skill for Codex from OutlineDriven/outline-driven-development. It costs 47 tokens per session (950 once invoked), scanned A, original, Apache-2.0.

A structured planning process that reviews an idea from business, design, developer-experience, and engineering perspectives, then turns it into an approved task list.

In plain words
What is it for?
It helps refine plans, create an append-only JSONL task ledger, update TODOs, and present the result for human approval.
Why use it?
It reduces gaps in a plan and gives implementation work stable task IDs that can be tracked over time.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit It helps refine plans, create an append-only JSONL task ledger, update TODOs, and present the result for human approval.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/outlinedriven/outline-driven-development/autoplan
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add OutlineDriven/outline-driven-development --skill autoplan
Clone the repo
git clone --depth 1 https://github.com/OutlineDriven/outline-driven-development

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for autoplan

README.md
[![agentmods](https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/autoplan.svg)](https://agentmods.dev/skills/outlinedriven/outline-driven-development/autoplan)
Your own site
<a href="https://agentmods.dev/skills/outlinedriven/outline-driven-development/autoplan"><img src="https://agentmods.dev/badge/skills/outlinedriven/outline-driven-development/autoplan.svg" alt="Measured on agentmods" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 950 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00047 $0.00950
Opus 5 $0.00023 $0.00475
Sonnet 5 $0.00009 $0.00190
Haiku 4.5 $0.00005 $0.00095

Measured yesterday against content hash 7a9cac991140, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

autoplan scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.devin/skills/autoplan/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Autoplan

Contract

Field Bound contract
Trigger The user runs /autoplan on a plan or idea.
Authority Reversible local: writes only the amended plan, the task JSONL ledger at tasks/autoplan-ledger.jsonl, and TODO updates; rollback is discarding those local artifacts. No remote mutation.
Side effect Writes the amended plan, appends tasks to tasks/autoplan-ledger.jsonl, and updates TODOs.
Done The final approval gate presents an amended plan and aggregated implementation tasks with stable IDs.

Inputs

Required: a plan or idea to develop, supplied as a file path or inline text.

Optional: an existing tasks/autoplan-ledger.jsonl to extend. If absent, create one.

Ledger destination and overwrite policy

The task ledger lives at tasks/autoplan-ledger.jsonl. When the file does not exist, create it. When it exists, append new tasks to the end; never overwrite or truncate existing entries. Each run appends only the tasks it produces. This preserves prior runs and makes the ledger append-only across invocations.

Task ID generation

Each task gets a deterministic ID formed from the reviewing phase prefix and a zero-padded sequence number within that phase:

  • CEO review: CEO-01, CEO-02, ...
  • Design review: DES-01, DES-02, ...
  • DX review: DX-01, DX-02, ...
  • Engineering review: ENG-01, ENG-02, ...

Sequence numbers start at 01 within each phase and increment in the order tasks are identified. IDs are stable within a run: the same plan evaluated the same way produces the same IDs. If a phase produces no tasks, its prefix is unused.

Each ledger line is a JSON object with id, description, and phase keys.

Procedure

  1. Read the supplied plan or idea. If it is a path, read the file; if inline text, use it directly. Stop if no plan or idea is supplied. Done when: the plan or idea is read or the absence is reported.
  2. Run the four review phases (CEO, design, DX, engineering), each evaluating the idea against a six-principle decision register (clarity, impact, audience, risk, sequencing, reversibility). Record each phase's decisions in the register. If a phase cannot reach a decision, record the open question and continue the remaining phases. Done when: all four phases have recorded their decisions or open questions in the register.
  3. Amend the plan with the consolidated decisions from all four phases. Done when: the plan is amended with consolidated decisions.
  4. Derive implementation tasks from the four phases. Assign deterministic IDs per the task ID generation rules above. Construct the task ledger by appending one JSON line per task to tasks/autoplan-ledger.jsonl, creating the file if absent. Update TODOs to reflect the aggregated tasks. Done when: the ledger is appended with one task per line, each carrying a stable ID, description, and phase, and TODOs reflect the aggregated tasks.
  5. Present the amended plan and aggregated tasks at a final approval gate. Stop and wait for the human decision; do not proceed to execution. Done when: the approval gate is presented and the skill stops for the human decision.

Read the full file on GitHub · 58 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday Changed · -24 tokens per session 7a9cac991140
  2. 4d ago First seen · 58 lines · 71 tokens per session scan A 8f412841dedb

Subscribe to this mod's changes

autoplan is a skill published in the GitHub repository OutlineDriven/outline-driven-development (52 stars, last pushed 2d ago), licensed Apache-2.0. It adds 47 tokens to every session and 950 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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