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.
npx agentmods add skills/codeaholicguy/ai-devkit/dev-planningnpx skills add codeaholicguy/ai-devkit --skill dev-planninggit clone --depth 1 https://github.com/codeaholicguy/ai-devkitWhat 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.
| Model | Per session | Once 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 |
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.
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
- Run
npx ai-devkit@latest lintbefore phase work. - If working on a named feature, run
npx ai-devkit@latest lint --feature <name>. - Read existing configured planning, implementation, and testing docs before changes. Resolve paths through
lint --featureinstead of assumingdocs/ai. - Keep task creation and updates traceable to requirements, design, testing scenarios, completed work, blockers, or newly discovered scope.
- If parent
dev-lifecycleestablished usable task tracing, emit planning phase, progress, blocker/scope, and next-step events pertask.
Create Initial Plan
Use for Phase 4 after requirements, design, and initial testing docs exist.
- Run
npx ai-devkit@latest lint --feature <name>and identify the planning doc path it validates. Ifdocs init-featurejust ran, use the returned planning path as authoritative. - Read requirements, design, and testing docs for the feature.
- Convert goals, user stories, design components, API/data changes, migration needs, and testing scenarios into implementation tasks.
- Group tasks by milestone or logical sequence.
- For each task, include outcome, dependencies, validation evidence, and related testing scenarios.
- Verify every test-plan scenario has at least one implementation task.
- Add risks, blockers, sequencing notes, and likely follow-up checks.
- Update the planning doc with the initial ordered task list.
- 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.
- 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.jsonpaths.docs, falling back todocs/ai. - If continuing from implementation, carry forward existing context. Otherwise ask for feature name, completed tasks, new tasks, blockers, and planning doc path.
- Review existing milestones, sequencing, dependencies, and outstanding tasks.
- Reconcile each task: mark status as done, in-progress, blocked, or not started; note scope changes; record blockers; capture skipped or added tasks.
- Update the planning doc with the current status checklist.
- Suggest the next 2-3 actionable tasks, risky areas, and coordination needed.
- If task tracing is available, record completed/blocked/new tasks, blockers, and next action per
task. - Write a summary paragraph for the planning doc covering progress, risks, upcoming focus, and scope changes.
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.
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.
- yesterday First seen · 48 lines · 54 tokens per session scan A e112492287b3
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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