LobsterAI is an open-source desktop AI agent that operates files, commands, browsers, documents, spreadsheets, slides, messaging channels, and scheduled jobs in a user's working environment. It supports office work, research, and custom multi-agent workflows, while catalogue add-ons extend the agent with additional skills and workflows.
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 skills add netease-youdao/LobsterAI --skill create-plangit clone --depth 1 https://github.com/netease-youdao/LobsterAIWrote 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.
[](https://agentmods.dev/skills/netease-youdao/lobsterai/create-plan)<a href="https://agentmods.dev/skills/netease-youdao/lobsterai/create-plan"><img src="https://agentmods.dev/badge/skills/netease-youdao/lobsterai/create-plan/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/netease-youdao/lobsterai/create-plan"><img src="https://agentmods.dev/badge/skills/netease-youdao/lobsterai/create-plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.00614 |
| Opus 5 | $0.00012 | $0.00307 |
| Sonnet 5 | $0.00005 | $0.00123 |
| Haiku 4.5 | $0.00002 | $0.00061 |
Grade A, and why
create-plan 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 10d ago.
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.
Copies of this mod
2 near-identical copies found in the catalogue:
- create-plan — 100% identical, 0 lines differ
- create-plan — 98% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Plan
Goal
Turn a user prompt into a single, actionable plan delivered in the final assistant message.
Minimal workflow
Throughout the entire workflow, operate in read-only mode. Do not write or update files.
-
Scan context quickly
- Read
README.mdand any obvious docs (docs/,CONTRIBUTING.md,ARCHITECTURE.md). - Skim relevant files (the ones most likely touched).
- Identify constraints (language, frameworks, CI/test commands, deployment shape).
- Read
-
Ask follow-ups only if blocking
- Ask at most 1–2 questions.
- Only ask if you cannot responsibly plan without the answer; prefer multiple-choice.
- If unsure but not blocked, make a reasonable assumption and proceed.
-
Create a plan using the template below
- Start with 1 short paragraph describing the intent and approach.
- Clearly call out what is in scope and what is not in scope in short.
- Then provide a small checklist of action items (default 6–10 items).
- Each checklist item should be a concrete action and, when helpful, mention files/commands.
- Make items atomic and ordered: discovery → changes → tests → rollout.
- Verb-first: “Add…”, “Refactor…”, “Verify…”, “Ship…”.
- Include at least one item for tests/validation and one for edge cases/risk when applicable.
- If there are unknowns, include a tiny Open questions section (max 3).
-
Do not preface the plan with meta explanations; output only the plan as per template
Plan template (follow exactly)
# Plan
<1–3 sentences: what we’re doing, why, and the high-level approach.>
## Scope
- In:
- Out:
## Action items
[ ] <Step 1>
[ ] <Step 2>
[ ] <Step 3>
[ ] <Step 4>
[ ] <Step 5>
[ ] <Step 6>
## Open questions
- <Question 1>
- <Question 2>
- <Question 3>
Checklist item guidance
Good checklist items:
- Point to likely files/modules: src/..., app/..., services/...
- Name concrete validation: “Run npm test”, “Add unit tests for X”
- Include safe rollout when relevant: feature flag, migration plan, rollback note
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.
- 10d ago First seen · 76 lines · 23 tokens per session scan A cc56e80de14a
create-plan is a skill published in the GitHub repository netease-youdao/LobsterAI (5,999 stars, last pushed yesterday), licensed MIT. It adds 23 tokens to every session and 614 once invoked, about $0.0001 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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