dev-planning

A planning guide for software feature work using AI DevKit documentation. It helps create and reconcile task plans across requirements, design, implementation, and testing.

In plain words
What is it for?
Creating feature plans, updating planning documents, recording progress or blockers, reconciling new tasks, and running the required AI DevKit checks before planning work.
Why use it?
It keeps planned work linked to requirements and test scenarios, making progress and blockers easier to track. It also checks that changes follow the project’s configured documentation paths.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/codeaholicguy/ai-devkit/dev-planning
Any agent
npx skills add codeaholicguy/ai-devkit --skill dev-planning
Clone the repo
git clone --depth 1 https://github.com/codeaholicguy/ai-devkit

Made for: Claude Code, Codex.

Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 696 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00054 $0.00696
Opus 5 $0.00027 $0.00348
Sonnet 5 $0.00011 $0.00139
Haiku 4.5 $0.00005 $0.00070

Measured yesterday against content hash e112492287b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dev-planning 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.

skills/dev-planning/SKILL.md · 48 lines

How it starts

The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dev Planning

Run planning creation and reconciliation for configured AI docs features. Before changing docs, propose the concrete plan for this phase and wait for user approval unless the user already approved the exact phase plan.

Phase Contract

  1. Run npx ai-devkit@latest lint before phase work.
  2. If working on a named feature, run npx ai-devkit@latest lint --feature <name>.
  3. Read existing configured planning, implementation, and testing docs before changes. Resolve paths through lint --feature instead of assuming docs/ai.
  4. Keep task creation and updates traceable to requirements, design, testing scenarios, completed work, blockers, or newly discovered scope.
  5. If parent dev-lifecycle established usable task tracing, emit planning phase, progress, blocker/scope, and next-step events per task.

Create Initial Plan

Use for Phase 4 after requirements, design, and initial testing docs exist.

  1. Run npx ai-devkit@latest lint --feature <name> and identify the planning doc path it validates. If docs init-feature just ran, use the returned planning path as authoritative.
  2. Read requirements, design, and testing docs for the feature.
  3. Convert goals, user stories, design components, API/data changes, migration needs, and testing scenarios into implementation tasks.
  4. Group tasks by milestone or logical sequence.
  5. For each task, include outcome, dependencies, validation evidence, and related testing scenarios.
  6. Verify every test-plan scenario has at least one implementation task.
  7. Add risks, blockers, sequencing notes, and likely follow-up checks.
  8. Update the planning doc with the initial ordered task list.
  9. If task tracing is available, record plan progress and next implementation step per task.

Next: dev-implementation.

Update Planning

Use for Phase 6. Auto-trigger this phase after completing any task in dev-implementation.

  1. Run npx ai-devkit@latest lint --feature <name> and reconcile the planning doc path it validates. If manual path resolution is unavoidable, first resolve .ai-devkit.json paths.docs, falling back to docs/ai.
  2. If continuing from implementation, carry forward existing context. Otherwise ask for feature name, completed tasks, new tasks, blockers, and planning doc path.
  3. Review existing milestones, sequencing, dependencies, and outstanding tasks.
  4. Reconcile each task: mark status as done, in-progress, blocked, or not started; note scope changes; record blockers; capture skipped or added tasks.
  5. Update the planning doc with the current status checklist.
  6. Suggest the next 2-3 actionable tasks, risky areas, and coordination needed.
  7. If task tracing is available, record completed/blocked/new tasks, blockers, and next action per task.
  8. Write a summary paragraph for the planning doc covering progress, risks, upcoming focus, and scope changes.

Read the full file on GitHub · 48 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 First seen · 48 lines · 54 tokens per session scan A e112492287b3

Subscribe to this mod's changes

dev-planning is a skill published in the GitHub repository codeaholicguy/ai-devkit (1,601 stars, last pushed 2d ago), licensed MIT. It adds 54 tokens to every session and 696 once invoked, about $0.0003 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 2026-08-30.

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