Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/junevm/splathash/planning-with-files)<a href="https://agentmods.dev/skills/junevm/splathash/planning-with-files"><img src="https://agentmods.dev/badge/skills/junevm/splathash/planning-with-files.svg" alt="Measured on agentmods" 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 | $0.00069 | $0.01904 |
| Opus 5 | $0.00034 | $0.00952 |
| Sonnet 5 | $0.00014 | $0.00381 |
| Haiku 4.5 | $0.00007 | $0.00190 |
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 4d 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.
This is a copy
94% identical to planning-with-files — 19 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planning with Files
Work like Manus: Use persistent markdown files as your "working memory on disk."
FIRST: Check for Previous Session (v2.2.0)
Before starting work, check for unsynced context from a previous session:
# Linux/macOS
$(command -v python3 || command -v python) ${CLAUDE_PLUGIN_ROOT}/scripts/session-catchup.py "$(pwd)"
# Windows PowerShell
& (Get-Command python -ErrorAction SilentlyContinue).Source "$env:USERPROFILE\.claude\skills\planning-with-files\scripts\session-catchup.py" (Get-Location)
If catchup report shows unsynced context:
- Run
git diff --statto see actual code changes - Read current planning files
- Update planning files based on catchup + git diff
- Then proceed with task
Important: Where Files Go
- Templates are in
${CLAUDE_PLUGIN_ROOT}/templates/ - Your planning files go in your project directory
| Location | What Goes There |
|---|---|
Skill directory (${CLAUDE_PLUGIN_ROOT}/) |
Templates, scripts, reference docs |
| Your project directory | task_plan.md, findings.md, progress.md |
Quick Start
Before ANY complex task:
- Create
task_plan.md— Use templates/task_plan.md as reference - Create
findings.md— Use templates/findings.md as reference - Create
progress.md— Use templates/progress.md as reference - Re-read plan before decisions — Refreshes goals in attention window
- Update after each phase — Mark complete, log errors
Note: Planning files go in your project root, not the skill installation folder.
The Core Pattern
Context Window = RAM (volatile, limited)
Filesystem = Disk (persistent, unlimited)
→ Anything important gets written to disk.
File Purposes
| File | Purpose | When to Update |
|---|---|---|
task_plan.md |
Phases, progress, decisions | After each phase |
findings.md |
Research, discoveries | After ANY discovery |
progress.md |
Session log, test results | Throughout session |
What ships with it
7 files 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.
- 4d ago First seen · 242 lines · 69 tokens per session scan A 25c4b3b6ceb5
planning-with-files is a skill published in the GitHub repository junevm/splathash (208 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 1,904 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to planning-with-files, differing in 19 lines, and is treated as a copy.
Other skills, from other repositories
meme-sticker
Turn one uploaded image into a complete 12-piece chat sticker pack by generating two 3x2 sticker sheets, extracting transparent PNGs, normalizing their canvases, and packaging the result as a ZIP. Use this skill whenever a user provides a photo and asks for chat stickers, reaction stickers, meme stickers, custom…
Telegram Custom Emoji Mosaic
Use when the user wants an image posted to Telegram as a custom-emoji mosaic — an emoji "painting" for a channel post — or asks to turn a picture into custom emoji, build an emoji pack from an image, or make an emoji banner.
image-audit
对图片进行鉴黄、政治、暴恐内容审核。先将图片压缩到 500px/JPEG 后直传 NX API 审核,以表格汇总结果。适用于用户提到图片审核、内容检查、鉴黄、政治识别、暴恐识别、违规扫描、图片安全、JPG/PNG/WebP 审核的场景。.
image-compress
对图片进行智能压缩优化。支持本地路径、文件夹和远程 URL,直传 NX API 压缩后返回 CDN 地址和压缩率。适用于用户提到图片压缩、图片优化、减小图片体积、TinyPNG、JPG/PNG/WebP 压缩的场景。.
studiomcphub-studio
Image to Retail in 90 seconds. 10-stage creative pipeline: background removal, palette extraction, resize, 6-product mockups, CMYK conversion, print-ready PDF, SVG vectorization, invisible watermarking, AI metadata enrichment, ESRGAN upscaling. Local DAM organizes all outputs. HTML preview gallery.
use-openhcs
Operate local OpenHCS microscopy workflows through the bundled MCP server. Use when Codex needs to inspect plate data, discover processing functions, author or validate pipelines, compile and execute jobs, control viewers, or interact with a running OpenHCS GUI.