Plan Review Criteria
penpot/penpot
Plan review criteria — the six review axes, severity rubric, approval standard, and output format for reviewing implementation plans.
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream consumers can execute without guessing.
MITAuto-check passed
Install LLM Friendly Context
$ npx skills add shinpr/claude-code-workflows --skill llm-friendly-context -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install shinpr/claude-code-workflows llm-friendly-context --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/shinpr/claude-code-workflows.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/llm-friendly-context .claude/skills/llm-friendly-context && 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 "llm-friendly-context" agent skill from https://github.com/shinpr/claude-code-workflows/tree/main/skills/llm-friendly-context into .claude/skills/llm-friendly-context/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-friendly-context", 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/shinpr/claude-code-workflows/tree/main/skills/llm-friendly-contextType 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 shinpr/claude-code-workflows --skill llm-friendly-context -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install shinpr/claude-code-workflows llm-friendly-context --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shinpr/claude-code-workflows.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/llm-friendly-context .agents/skills/llm-friendly-context && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "llm-friendly-context" agent skill from https://github.com/shinpr/claude-code-workflows/tree/main/skills/llm-friendly-context into .agents/skills/llm-friendly-context/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-friendly-context", 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 shinpr/claude-code-workflows --skill llm-friendly-context -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install shinpr/claude-code-workflows llm-friendly-context --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shinpr/claude-code-workflows.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/llm-friendly-context .cursor/skills/llm-friendly-context && 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 "llm-friendly-context" agent skill from https://github.com/shinpr/claude-code-workflows/tree/main/skills/llm-friendly-context into .cursor/skills/llm-friendly-context/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-friendly-context", 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/shinpr/claude-code-workflows.git --path skills/llm-friendly-context--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 shinpr/claude-code-workflows --skill llm-friendly-context -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install shinpr/claude-code-workflows llm-friendly-context --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shinpr/claude-code-workflows.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/llm-friendly-context .gemini/skills/llm-friendly-context && 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 "llm-friendly-context" agent skill from https://github.com/shinpr/claude-code-workflows/tree/main/skills/llm-friendly-context into .gemini/skills/llm-friendly-context/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-friendly-context", 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 shinpr/claude-code-workflows llm-friendly-contextInstalls 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 shinpr/claude-code-workflows --skill llm-friendly-context -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/shinpr/claude-code-workflows.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/llm-friendly-context .github/skills/llm-friendly-context && 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 "llm-friendly-context" agent skill from https://github.com/shinpr/claude-code-workflows/tree/main/skills/llm-friendly-context into .github/skills/llm-friendly-context/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-friendly-context", 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 shinpr/claude-code-workflows --skill llm-friendly-context -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install shinpr/claude-code-workflows llm-friendly-context --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/shinpr/claude-code-workflows.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/llm-friendly-context .opencode/skills/llm-friendly-context && 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 "llm-friendly-context" agent skill from https://github.com/shinpr/claude-code-workflows/tree/main/skills/llm-friendly-context into .opencode/skills/llm-friendly-context/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-friendly-context", 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.
Facts
- Skill name
llm-friendly-context- GitHub stars
- 693
- Token cost
- ~1.4k tokens
- SKILL.md length
- 690 words
- Files
- 1
- Skills in repo
- 30
- Repo updated
- First seen
- Licence
- MIT
At a glance
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream consumers can execute without guessing.
- Works in 7 steps: Use positive, executable instructions → Make vague instructions concrete → Specify output shape → …
- Revising LLM-facing prompts
- SKILL.md covers Core Rules, Rewrite Patterns, Handoff Checklist and Generated Artifact Checklist
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
LLM Friendly Context is an agent skill from shinpr/claude-code-workflows. Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream consumers can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: Development workflows for Claude Code that keep broad exploration focused on the outcome you approved. The licence is MIT.
When your agent uses it
- Revising LLM-facing prompts
- Planning artifacts
- Generated instructions
Example prompts
- “Use the llm-friendly-context skill to clarify inputs, outputs, success criteria, decisions, and unresolved conditions so downstream consumers can…”
- “/llm-friendly-context”
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Use positive, executable instructions
- Make vague instructions concrete
- Specify output shape
- Provide the smallest sufficient context
- Decompose complex work into verifiable steps
- Permit uncertainty explicitly
- Keep constraints proportionate
What it can do on your machine
Read from SKILL.md and the folder at commit a4ecd62. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
LLM Friendly Context loads about 1.4k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 690 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.
Safety
Auto-check passed
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.
SKILL.md
The full file from shinpr/claude-code-workflows at commit a4ecd62, republished under its MIT licence (© shinpr). 690 words, ~1,383 tokens.
Download SKILL.mdSave it as
.claude/skills/llm-friendly-context/SKILL.md (or your agent's skills folder).- name
- llm-friendly-context
- description
- Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream consumers can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
LLM-Friendly Context
The goal is stable downstream execution: the next consumer should know what to read, what to do, what counts as success, and which unresolved decisions can change the result.
Core Rules
Use positive, executable instructions
- State what the next consumer should do.
- Convert quality policies into positive criteria.
- Keep a prohibition only when it protects an irreversible boundary or shipped contract. Name the protected condition and the allowed action.
- Example: "Preserve existing public API behavior across the documented compatibility cases."
Make vague instructions concrete
- Replace subjective terms with observable conditions, paths, commands, schemas, examples, or decision rules.
- Terms that often need clarification when they leave a decision to the next consumer:
appropriate,proper,related,existing behavior,optional,as needed,if needed,per convention, unresolved alternatives,TBD,placeholder.
Specify output shape
- Use the sections, fields, table columns, JSON keys, or checklist items the consumer uses.
- For handoffs, include only produced artifact paths and status fields that control the next transition.
Provide the smallest sufficient context
- Sufficient means sufficient for the assigned action, not complete background: every item you include is consumed by that action or by the result it must produce.
- Include the purpose, source artifacts, hard constraints, accepted decisions, and unresolved conditions that action consumes.
- Prefer concrete file paths and section hints over broad module names.
- Follow references while they can change an in-scope decision, action, or verification result.
Decompose complex work into verifiable steps
- Split work with 3+ objectives or sequential dependencies into ordered steps.
- Each step needs a checkpoint: what evidence proves it is complete.
Permit uncertainty explicitly
- Resolve missing operational detail from referenced artifacts and repository evidence before treating it as unresolved.
- Record remaining uncertainty with its effect, required input, and decision owner. Make reversible repository-local choices when governing evidence resolves them.
Keep constraints proportionate
- Add only constraints that reduce ambiguity or preserve a real requirement.
- Keep simple downstream tasks lightweight when the target action, context, and success criteria are already clear.
- Apply
minimal,a few lines, and explicit line estimates to the completed diff as one total budget.
Show full SKILL.md (339 more words)Show less
Rewrite Patterns
Use these rewrites before treating a prompt, handoff, or artifact as complete.
| Ambiguous form | Rewrite as |
|---|---|
optional used as an unresolved choice | Required, omitted, or required only under a named condition |
| Multiple alternatives that the next consumer must choose between | The selected option, or a deterministic decision rule |
as needed / if needed | The triggering condition and required action |
per convention | The file, function, test, or documented convention to follow |
related files | Specific paths, globs, or search hints |
existing behavior | The observable behavior, source file, test, API response, or UI state to preserve |
placeholder | Exact temporary value/behavior, allowed dependencies, and verification expectation |
TBD used as a placeholder for required information | A blocking unresolved item with owner, required input, and decision effect |
appropriate / proper | A measurable criterion or checklist |
Handoff Checklist
Before sending a prompt or artifact to another consumer, verify:
- The target action is explicit.
- Required input paths, source artifacts, and decision-relevant facts are named.
- Every included context item is consumed by the target action or its required result.
- Accepted decisions and constraints use one canonical wording.
- Output format or expected status fields are specified.
- Success criteria are observable.
- Ambiguous expressions have been rewritten or marked as unresolved.
- Each instruction states the allowed action; each retained prohibition names the protected condition and allowed alternative.
- The next consumer can complete its scope from the supplied purpose, sources, criteria, and evidence, or return the exact unresolved decision and owner.
Generated Artifact Checklist
Before writing or finalizing a generated document:
- Each requirement, claim, task, test skeleton, or review finding has enough source context to trace why it exists.
- Every executable instruction names the target, action, and expected result.
- Verification steps say what to run or observe and what result proves success.
- Each instruction states the allowed action; each retained prohibition names the protected condition and allowed alternative.
- If an artifact is derived from another artifact, copied decisions stay consistent in wording and meaning.
- If downstream work is blocked by missing information, the artifact records the missing input, decision owner, and effect.
© shinpr, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/llm-friendly-context of shinpr/claude-code-workflows.
Open the folder on GitHubat commit a4ecd62
Compare with similar skills
LLM Friendly Context 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 |
|---|---|---|---|---|---|---|
| LLM Friendly Context this skillshinpr/claude-code-workflows | 693 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Plan Review Criteriapenpot/penpot | 61k | — | ~3.3k | Automated safety check: Pass | MPL-2.0 | |
| Search Inputthedaviddias/Front-End-Checklist | 74k | — | ~402 | Automated safety check: Pass | MIT | |
| Input Typesthedaviddias/Front-End-Checklist | 74k | — | ~487 | Automated safety check: Pass | MIT | |
| Paste Inputsthedaviddias/Front-End-Checklist | 74k | — | ~443 | Automated safety check: Pass | MIT | |
| Form Follows Function Success Criteriahashgraph-online/awesome-codex-plugins | 1.3k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 |
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The resolution criteria for PostHog Review's resolution stage: the bar for deciding, per unresolved review thread, whether the ask is worth implementing and safe to implement unattended.
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Questions about LLM Friendly Context
What does LLM Friendly Context do?
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream consumers can execute without guessing. LLM Friendly Context is an agent skill from shinpr/claude-code-workflows. Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream consumers can execute without guessing.
When should I use LLM Friendly Context?
LLM Friendly Context fits situations like: revising LLM-facing prompts; planning artifacts; generated instructions.
How do I install LLM Friendly Context in Claude Code?
Run `npx skills add shinpr/claude-code-workflows --skill llm-friendly-context -a claude-code`. Or copy the skill folder (skills/llm-friendly-context in shinpr/claude-code-workflows) into .claude/skills/llm-friendly-context in your project. Claude Code loads it when a task matches its description.
How do I install LLM Friendly Context in Codex?
Run `npx skills add shinpr/claude-code-workflows --skill llm-friendly-context -a codex`. Or copy the skill folder (skills/llm-friendly-context in shinpr/claude-code-workflows) into .agents/skills/llm-friendly-context in your project. Codex loads it when a task matches its description.
Can I use LLM Friendly Context in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add shinpr/claude-code-workflows --skill llm-friendly-context -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/llm-friendly-context, .gemini/skills/llm-friendly-context, .github/skills/llm-friendly-context and .opencode/skills/llm-friendly-context in your project.
What does LLM Friendly Context need to run?
SKILL.md names no scripts, command-line tools or credentials: LLM Friendly Context is instructions for the agent only.
Does LLM Friendly Context access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is LLM Friendly Context safe to install?
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.
What licence does LLM Friendly Context use?
LLM Friendly Context is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does LLM Friendly Context use?
About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to LLM Friendly Context?
Skills that share tags, products or a category with LLM Friendly Context: Plan Review Criteria (penpot/penpot, 61k stars), Search Input (thedaviddias/Front-End-Checklist, 74k stars), Input Types (thedaviddias/Front-End-Checklist, 74k stars) and Paste Inputs (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains LLM Friendly Context?
shinpr (a GitHub user) maintains it in shinpr/claude-code-workflows, which has 693 GitHub stars. The repository holds 30 skills in this directory. The repository was last updated on October 1, 2026.
Source: shinpr/claude-code-workflows on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.