planning-with-files

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Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. Optional gated mode can request continuation only when the host supports it and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

Data & Documents 26,790 stars 2231 forks Updated yesterday MIT

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Quality Score: 96/100

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Documentation 15%
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Description 5%
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Skill Content

> Hermes note: lifecycle automation for this skill comes from the Hermes adapter plugin in `.hermes/plugins/planning-with-files/`. Install it with `hermes plugins install OthmanAdi/planning-with-files/.hermes/plugins/planning-with-files`, then `hermes plugins enable planning-with-files`. Full guide: docs/hermes.md in the repository. # Planning with Files Work like Manus: Use persistent markdown files as your "working memory on disk." ## FIRST: Restore Project State **Before doing anything else**, check if planning files exist and read them: 1. If `task_plan.md` exists (in the project root, or in the active `.planning/<plan>/` directory), read `task_plan.md`, `progress.md`, and `findings.md` immediately. The `planning_with_files_status` tool or `/pwf-status` names the active plan. 2. Run `git diff --stat` to see code changes that may not yet be recorded in the planning files. Automatic recovery stops there. The following optional command reads same-project local session records and emits aggregate counts only: ```bash # Linux/macOS — auto-detects the Hermes home (HERMES_HOME or the platform default) SKILL_DIR="${HERMES_HOME:-$HOME/.hermes}/skills/planning-with-files" [ -d "$SKILL_DIR" ] || SKILL_DIR="${LOCALAPPDATA:-}/hermes/skills/planning-with-files" $(command -v python3 || command -v python) "${SKILL_DIR}/scripts/session-catchup.py" --metadata "$(pwd)" ``` ```powershell # Windows PowerShell — native Windows Hermes keeps its home under %LOCALAPPDATA%\hermes $HermesDi...

Details

Author
OthmanAdi
Repository
OthmanAdi/planning-with-files
Created
8 months ago
Last Updated
yesterday
Language
Python
License
MIT

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Persistent file-based planning for multi-step AI-agent work. Keeps task_plan.md, findings.md, and progress.md on disk; lifecycle hooks inject selected project planning context. Automatic recovery reads project planning files only. Explicit session-catchup.py --metadata reads same-project local agent session records and emits aggregate counts only; --replay may emit bounded nonce-framed excerpts. Optional gated mode can request continuation only when the host supports it and never runs commands declared in Markdown. The skill has no network upload path. Use for research or work needing 5+ tool calls.

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Persistent file-based planning for complex work. Creates task_plan.md, findings.md, and progress.md. Use before substantive work when the user asks to save or write a plan and execute it, says “сохрани план и выполни”, “сначала запиши план”, or “большая задача”, requests a multi-step research/build/migration/audit likely to need 5+ tool calls, or the work must survive compaction, /clear, a provider limit, or a CLI switch.

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Manus-style persistent file-based planning for AI coding agents: keeps task_plan.md, findings.md, and progress.md on disk so work survives context loss and /clear. Use when asked to plan out, break down, or organize a multi-step project, research task, or any work requiring 5+ tool calls. Supports automatic session recovery after /clear.

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