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 midFang/ai-agent-skills-workflow --skill plangit clone --depth 1 https://github.com/midFang/ai-agent-skills-workflowWrote 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/midfang/ai-agent-skills-workflow/plan)<a href="https://agentmods.dev/skills/midfang/ai-agent-skills-workflow/plan"><img src="https://agentmods.dev/badge/skills/midfang/ai-agent-skills-workflow/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/midfang/ai-agent-skills-workflow/plan"><img src="https://agentmods.dev/badge/skills/midfang/ai-agent-skills-workflow/plan.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00097 | $0.00575 |
| Opus 5 | $0.00048 | $0.00287 |
| Sonnet 5 | $0.00019 | $0.00115 |
| Haiku 4.5 | $0.00010 | $0.00057 |
Grade A, and why
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 8d 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.
What it actually says
Plan
Use this skill as the replacement for the deprecated custom prompt /prompts:plan.
Invocation
Preferred explicit trigger:
$plan 帮我设计用户登录模块的实现方案
Natural-language triggers:
进入 Plan 模式先出执行计划帮我生成 plan 文件
Workflow
- Confirm the task and current workspace.
- Gather only the context needed to name concrete files, modules, or integration points.
- Start with 5-8 targeted read-only tool calls.
- Stop early once the implementation path is clear.
- Choose
simple,medium, orcomplexbased on scope and risk. - If
mcp__sequential-thinking__sequentialthinkingis available and the task is more than trivial, use it to shape the plan. - Create or update a plan file under the current workspace.
- New plan:
plan/YYYY-MM-DD_HH-mm-ss-<slug>.md - Existing plan: reuse the previous file when the user clearly says they want to adjust the earlier plan.
- New plan:
- The plan file frontmatter should include:
---
mode: plan
cwd: <current workspace>
task: <task summary>
complexity: <simple|medium|complex>
tool: mcp__sequential-thinking__sequentialthinking
total_thoughts: <final count>
created_at: <ISO8601 timestamp>
---
- The plan body should contain:
- A brief task summary
- A numbered execution plan
- Risks and blockers
path:linereferences where they materially help implementation
- Reply in concise Chinese using this shape:
🎯 任务📋 执行计划🧠 当前思考摘要⚠️ 风险与阻塞📎 Plan 文件
Defaults
- Prefer writing a
plan/*.mdfile instead of only chatting. - Keep the plan decision-complete so implementation can start without extra design decisions.
- Do not implement the plan unless the user explicitly switches from planning to execution.
- If file writes are blocked, return the full plan text plus the intended file path.
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.
- 8d ago First seen · 63 lines · 97 tokens per session scan A cef60f381ed7
plan is a skill published in the GitHub repository midFang/ai-agent-skills-workflow (2 stars, last pushed 2mo ago), licensed MIT. It adds 97 tokens to every session and 575 once invoked, about $0.0005 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 2026-08-31.
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