Skill Compose is an open-source platform for building and running AI agents that use modular skills. It is intended for creating skill-powered agents without workflow graphs or a command-line interface, and the catalogue skills are examples of those agent capabilities.
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/dp-archive/archive/planning-with-files)<a href="https://agentmods.dev/skills/dp-archive/archive/planning-with-files"><img src="https://agentmods.dev/badge/skills/dp-archive/archive/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 | $0.00056 | $0.01899 |
| Opus 5 | $0.00028 | $0.00949 |
| Sonnet 5 | $0.00011 | $0.00380 |
| Haiku 4.5 | $0.00006 | $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 9d 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
8 near-identical copies found in the catalogue:
- planning-with-files — 100% identical, 4 lines differ
- planning-with-files — 100% identical, 20 lines differ
- planning-with-files — 94% identical, 19 lines differ
- planning-with-files — 89% identical, 30 lines differ
- planning-with-files — 89% identical, 16 lines differ
- planning-with-files — 83% identical, 45 lines differ
- planning-with-files — 80% identical, 35 lines differ
- planning-with-files — 80% identical, 112 lines differ
How it starts
The opening of the file, as written. The whole thing — 249 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 (auto-detects python3 or python)
$(command -v python3 || command -v python) ${CLAUDE_PLUGIN_ROOT}/scripts/session-catchup.py "$(pwd)"
# Windows PowerShell
python "$env:USERPROFILE\.opencode\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
5 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.
- 9d ago First seen · 249 lines · 56 tokens per session scan A 185b4a6be263
planning-with-files is a skill published in the GitHub repository dp-archive/archive (1,107 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 1,899 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…