Guidelines
akash-network/node
Behavioral guidelines to reduce common LLM coding mistakes. An agent skill from akash-network/node.
On an explicit planning request, always call readskill for this skill before answering.
$ npx skills add asgeirtj/system_prompts_leaks --skill plan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install asgeirtj/system_prompts_leaks plan --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/asgeirtj/system_prompts_leaks.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Meta/muse-code/skills/plan .claude/skills/plan && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "plan" agent skill from https://github.com/asgeirtj/system_prompts_leaks/tree/main/Meta/muse-code/skills/plan into .claude/skills/plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "plan", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/asgeirtj/system_prompts_leaks/tree/main/Meta/muse-code/skills/planType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add asgeirtj/system_prompts_leaks --skill plan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install asgeirtj/system_prompts_leaks plan --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgeirtj/system_prompts_leaks.git skills-src && mkdir -p .agents/skills && cp -r skills-src/Meta/muse-code/skills/plan .agents/skills/plan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "plan" agent skill from https://github.com/asgeirtj/system_prompts_leaks/tree/main/Meta/muse-code/skills/plan into .agents/skills/plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "plan", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgeirtj/system_prompts_leaks --skill plan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install asgeirtj/system_prompts_leaks plan --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgeirtj/system_prompts_leaks.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/Meta/muse-code/skills/plan .cursor/skills/plan && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "plan" agent skill from https://github.com/asgeirtj/system_prompts_leaks/tree/main/Meta/muse-code/skills/plan into .cursor/skills/plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "plan", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/asgeirtj/system_prompts_leaks.git --path Meta/muse-code/skills/plan--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add asgeirtj/system_prompts_leaks --skill plan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install asgeirtj/system_prompts_leaks plan --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgeirtj/system_prompts_leaks.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/Meta/muse-code/skills/plan .gemini/skills/plan && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "plan" agent skill from https://github.com/asgeirtj/system_prompts_leaks/tree/main/Meta/muse-code/skills/plan into .gemini/skills/plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "plan", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install asgeirtj/system_prompts_leaks planInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add asgeirtj/system_prompts_leaks --skill plan -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/asgeirtj/system_prompts_leaks.git skills-src && mkdir -p .github/skills && cp -r skills-src/Meta/muse-code/skills/plan .github/skills/plan && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "plan" agent skill from https://github.com/asgeirtj/system_prompts_leaks/tree/main/Meta/muse-code/skills/plan into .github/skills/plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "plan", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgeirtj/system_prompts_leaks --skill plan -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install asgeirtj/system_prompts_leaks plan --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgeirtj/system_prompts_leaks.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/Meta/muse-code/skills/plan .opencode/skills/plan && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "plan" agent skill from https://github.com/asgeirtj/system_prompts_leaks/tree/main/Meta/muse-code/skills/plan into .opencode/skills/plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "plan", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
planOn an explicit planning request, always call readskill for this skill before answering.
Plan is an agent skill from asgeirtj/system_prompts_leaks. On an explicit planning request, always call readskill for this skill before answering. Research first, then return one concise inline plan; do not create a plan file unless the user explicitly asks or a governing workflow requires one. Start and end the reply by saying this is not a special mode and go executes the plan; do not implement in the planning turn. For ordinary implement, build, fix, debug, or refactor requests, work directly. When an explicit plan divides work into separate diffs, commits, or PRs and…
Its SKILL.md is about 5.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Refactoring. The repository describes itself as: Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro… The licence is CC0-1.0.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit e31ec21. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
gitFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Plan loads about 5.1k tokens when it runs. Until then it costs about 153 tokens; SKILL.md has 2,936 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from asgeirtj/system_prompts_leaks at commit e31ec21, republished under its CC0-1.0 licence (© asgeirtj). 2,936 words, ~5,144 tokens.
.claude/skills/plan/SKILL.md (or your agent's skills folder).Create a grounded, decision-complete plan before complex work.
For an explicit plan, follow these steps in order. Do not write plan prose or a plan file until the applicable research in steps 1-5 is complete:
request_user_input, research any
factual unknown that could eliminate the question; this may include bounded,
preference-independent external research. Do not ask merely because scope, platform,
or experience is unspecified. Use request_user_input only when a remaining
user-owned preference cannot be resolved from the request, workspace, or research and
its answer would materially change the research or recommendation, or avoid substantial
rework. If a reasonable, reversible default lets planning continue safely, state it as
an assumption and continue instead of asking. Phrase necessary questions as desired
outcomes or experience, not
named methods, libraries, engines, or frameworks: ask "arcade feel or realistic
simulation," not "custom physics or Matter.js." Research and recommend the technical
implementation yourself. When input is necessary, ask only one necessary question per
turn. Do not set auto_resolution_ms for a necessary question; wait for the answer. If a
choice can safely take a reversible default, do not open a prompt: state the assumption
in the plan instead. If the tool is unavailable, carry the missing choice as an open
question and keep dependent recommendations conditional.Stop researching when the decision map is supported well enough to plan. Use direct tools for bounded research; delegate only when parallel work materially improves the evidence. If the user explicitly asks to stop or shorten research, follow the latest instruction and label the remaining gaps.
A plan is ready only when it is:
Deliver the plan inline by default. Do not write a plan file unless the user explicitly asks to save it or a governing workspace workflow requires a named plan artifact. Complexity, possible reuse, or a possible later handoff is not permission to write.
When persistence is authorized:
specs/<feature>/plan.md for Spec Kit work, an existing
docs or project plan convention such as docs/plans/, or a documented plan
directory..agents/plans/YYYY-MM-DD-<slug>.md.specs/<feature>/plan.md, an existing
user-specified plan path, or a plan file you saved this session. Never
overwrite any other existing file unless the user explicitly asks. When
creating a new dated file and the chosen file exists, add a short numeric
suffix./tmp for the final plan. Temporary scratch is not a durable user
artifact.Start the final reply with this exact sentence on one line so the next action stays visible even when a long plan is collapsed:
This is a plan, not a special mode; I haven’t started implementation. Reply go to execute this plan, or tell me what to change.
Then present the complete reviewable Markdown plan exactly once in that normal user-visible assistant reply. Saving or rereading a plan file is not presenting it.
Use one canonical Markdown plan body. Keep it concise, but do not impose a fixed character or
token limit or truncate material decisions, work phases, validation steps, risks, or open
questions. Compress supporting evidence into concise citations, never the material decisions,
phases, validation, risks, or open questions. If you save a plan file, its content must be
exactly the canonical body. Copy the canonical body verbatim into the normal assistant reply.
Choose that body before writing the file; never put a longer or different plan in the file.
Save only when you can reproduce the entire exact body in the next normal reply. If you cannot,
skip the file and deliver the complete plan inline. Do not create two independently expanded
versions of the plan. If you save the plan, put its path after the visible plan. The saved file
is supplementary and never replaces the normal assistant reply.
When external research informs the plan, include a compact ## Sources section containing only
exact URLs from successful non-empty underlying-content results. Each material external decision
must cite one of those URLs.
Before delivery:
head, a partial range, or another truncated read, then check the user's
constraints, Key Decisions, Work Plan, and Validation Plan for contradictions.After delivery:
request_user_input for the final handoff. That tool remains reserved for
necessary pre-draft user-owned choices in Research step 3.go to execute this plan,
or tell me what to change.”go, execute the preceding plan directly without regenerating it. On a change request,
revise and present the complete plan again.Write the plan so the next person can act without guessing. Use the smallest subset of this shape that carries the decisions needed for execution:
## Goal
## Success Criteria
## Approach
## Steps
## Validation Plan
## Risks / Open Questions (only when material)Write None for open questions only after checking the repo for answers.
Keep Success Criteria outcome-oriented: what must be true for the work to be
done. Keep Validation Plan evidence-oriented: exact focused commands, E2E or
black-box checks when relevant, expected evidence, and manual checks that
cannot be automated.
Adapt the sections to the plan type:
Steps should name the code surfaces, data flow,
compatibility impact, existing utilities to reuse, and test strategy. Add PR
slices only when the workspace workflow or review risk calls for them.Do not invent an issue, spec, PR, or file path just to fill a section. If the workspace rules require them, cite the real item or state the missing prerequisite as an open question or blocker. Do not repeat background the user already knows or add empty sections. Keep the plan decision-complete enough that an implementer does not need to invent scope, interfaces, or verification.
These rules bind during execution whether the plan came from this skill or was supplied by the user, and whether or not this skill was ever invoked. If you loaded this skill at publish time, only this section applies — the planning restrictions above do not.
git add -p) or assign
the file to the earliest unit and say so.© asgeirtj, CC0-1.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in Meta/muse-code/skills/plan of asgeirtj/system_prompts_leaks.
Open the folder on GitHubat commit e31ec21
Plan next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Plan this skillasgeirtj/system_prompts_leaks | 69k | — | ~5.1k | Automated safety check: Pass | CC0-1.0 | |
| Guidelinesakash-network/node | 1.1k | 20 repos | ~577 | Automated safety check: Pass | MIT | |
| Component Refactoringlangflow-ai/langflow | 155k | — | ~3.5k | Automated safety check: Pass | MIT | |
| Migrate Core Code to Submodulestinyhumansai/openhuman | 42k | — | ~2.6k | Automated safety check: Pass | GPL-3.0 | |
| ast-grep Structural Searchcode-yeongyu/oh-my-openagent | 70k | — | ~3.3k | Automated safety check: Pass | MIT | |
| Systematic Code Refactoringluongnv89/claude-howto | 42k | — | ~3k | Automated safety check: Pass | MIT |
akash-network/node
Behavioral guidelines to reduce common LLM coding mistakes. An agent skill from akash-network/node.
langflow-ai/langflow
Refactor high-complexity React components in Langflow frontend.
tinyhumansai/openhuman
Plans and carries out moving non-host-specific code and its tests from the OpenHuman core into vendored tiny submodule libraries, then releases the submodule and re-pins the host.
code-yeongyu/oh-my-openagent
Searches and rewrites code by syntax-tree shape across 25 languages with ast-grep, for codemods, structural queries and YAML lint rules, using a Python wrapper script.
luongnv89/claude-howto
Guides refactoring in phases based on Martin Fowler's method: research, test coverage check, planning and small tested steps, with your approval at each phase.
skills-directory/skill-codex
A skill your agent uses when the user asks to run Codex CLI (codex exec, codex resume) or references OpenAI Codex for code analysis, refactoring, or automated editing
asgeirtj/system_prompts_leaks
Shows one digest of coding-agent sessions across your connected machines and lets you open, read, steer, approve, stop and close them, over Herdr, tmux or MSP.
asgeirtj/system_prompts_leaks
Diagnoses a Muse Code installation's own failures from binary and session evidence, instead of treating the report as an ordinary repository bug.
asgeirtj/system_prompts_leaks
A skill your agent uses whenever the user wants to create, read, edit, or manipulate Word documents (.docx) or Word templates (.dotx).
asgeirtj/system_prompts_leaks
Runs a goal as a project in which the agent coordinates separate agent threads, judging when to split the work, and interviews you first when nothing can be verified.
asgeirtj/system_prompts_leaks
Creates and validates a new native Muse plugin package in the current workspace, limited to five capability families, and leaves installation to you.
asgeirtj/system_prompts_leaks
A skill your agent uses when the user's prompt requires (1) researching a topic across multiple sources, comparing options or alternatives, analyzing trends or history, understanding markets or…
Categories
On an explicit planning request, always call readskill for this skill before answering. Plan is an agent skill from asgeirtj/system_prompts_leaks. On an explicit planning request, always call readskill for this skill before answering.
Plan fits situations like: tasks that involve Refactoring.
Run `npx skills add asgeirtj/system_prompts_leaks --skill plan -a claude-code`. Or copy the skill folder (Meta/muse-code/skills/plan in asgeirtj/system_prompts_leaks) into .claude/skills/plan in your project. Claude Code loads it when a task matches its description.
Run `npx skills add asgeirtj/system_prompts_leaks --skill plan -a codex`. Or copy the skill folder (Meta/muse-code/skills/plan in asgeirtj/system_prompts_leaks) into .agents/skills/plan in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add asgeirtj/system_prompts_leaks --skill plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/plan, .gemini/skills/plan, .github/skills/plan and .opencode/skills/plan in your project.
Going by SKILL.md and its folder, Plan needs the command-line tools its instructions call (git).
SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Plan is published under the CC0-1.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.1k tokens (SKILL.md is roughly 21k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Plan: Guidelines (akash-network/node, 1.1k stars), Component Refactoring (langflow-ai/langflow, 155k stars), Migrate Core Code to Submodules (tinyhumansai/openhuman, 42k stars) and ast-grep Structural Search (code-yeongyu/oh-my-openagent, 70k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
asgeirtj (a GitHub user) maintains it in asgeirtj/system_prompts_leaks, which has 69,211 GitHub stars. The repository holds 124 skills in this directory. The repository was last updated on October 8, 2026.
Source: asgeirtj/system_prompts_leaks on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.