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 zhaono1/agent-playbook --skill planning-with-filesgit clone --depth 1 https://github.com/zhaono1/agent-playbookWrote 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/zhaono1/agent-playbook/planning-with-files)<a href="https://agentmods.dev/skills/zhaono1/agent-playbook/planning-with-files"><img src="https://agentmods.dev/badge/skills/zhaono1/agent-playbook/planning-with-files/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/zhaono1/agent-playbook/planning-with-files"><img src="https://agentmods.dev/badge/skills/zhaono1/agent-playbook/planning-with-files.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 24 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00055 | $0.00709 |
| Opus 5 | $0.00028 | $0.00354 |
| Sonnet 5 | $0.00011 | $0.00142 |
| Haiku 4.5 | $0.00006 | $0.00071 |
Grade A, and why
planning-with-files 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planning with Files
"Work like Manus" — Uses persistent markdown files for planning, progress tracking, and knowledge storage.
Description
A skill that transforms your workflow to use persistent markdown files for planning and progress tracking.
The Problem
Claude Code (and most AI agents) suffer from:
- Volatile memory — TodoWrite tool disappears on context reset
- Goal drift — Original goals get forgotten after many tool calls
- Hidden errors — Failures aren't tracked, mistakes repeat
- Context stuffing — Everything crammed into context instead of stored
The Solution: 3-File Pattern
For every complex task, create THREE files:
task_plan.md → Track phases and progress
notes.md → Store research and findings
[deliverable].md → Final output
The Workflow Loop
1. Create task_plan.md with goal and phases
2. Research → save to notes.md → update task_plan.md
3. Read notes.md → create deliverable → update task_plan.md
4. Deliver final output
When to Use
Use this pattern for:
- Multi-step tasks (3+ steps)
- Research tasks
- Building/creating projects
- Tasks spanning many tool calls
- Anything requiring organization
Skip for:
- Simple questions
- Single-file edits
- Quick lookups
Installation
This skill is typically installed globally at ~/.claude/skills/planning-with-files/.
From this repository:
ln -s /path/to/agent-playbook/skills/planning-with-files ~/.claude/skills/planning-with-files
If you prefer the standalone workflow, see the upstream repository in the Links section.
The Manus Principles
| Principle | Implementation |
|---|---|
| Filesystem as memory | Store in files, not context |
| Attention manipulation | Re-read plan before decisions |
| Error persistence | Log failures in plan file |
| Goal tracking | Checkboxes show progress |
| Append-only context | Never modify history |
Example
You: "Research the benefits of TypeScript and write a summary"
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.
- 12d ago First seen · 110 lines · 55 tokens per session scan A 47bc15ce9690
planning-with-files is a skill published in the GitHub repository zhaono1/agent-playbook (77 stars, last pushed 17d ago), licensed MIT. It adds 55 tokens to every session and 709 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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