Vercel Composition Patterns
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
Facilitate a structured conversation to define requirement standards for a project — epic and feature definitions, scenario structure, AC format, priority notation, status workflow, and naming…
$ npx skills add techygarg/lattice --skill requirement-forge-refiner -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install techygarg/lattice requirement-forge-refiner --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/techygarg/lattice.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/requirement-forge-refiner .claude/skills/requirement-forge-refiner && 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 "requirement-forge-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/requirement-forge-refiner into .claude/skills/requirement-forge-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "requirement-forge-refiner", 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/techygarg/lattice/tree/main/skills/requirement-forge-refinerType 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 techygarg/lattice --skill requirement-forge-refiner -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install techygarg/lattice requirement-forge-refiner --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/requirement-forge-refiner .agents/skills/requirement-forge-refiner && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "requirement-forge-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/requirement-forge-refiner into .agents/skills/requirement-forge-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "requirement-forge-refiner", 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 techygarg/lattice --skill requirement-forge-refiner -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install techygarg/lattice requirement-forge-refiner --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/requirement-forge-refiner .cursor/skills/requirement-forge-refiner && 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 "requirement-forge-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/requirement-forge-refiner into .cursor/skills/requirement-forge-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "requirement-forge-refiner", 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/techygarg/lattice.git --path skills/requirement-forge-refiner--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 techygarg/lattice --skill requirement-forge-refiner -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install techygarg/lattice requirement-forge-refiner --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/requirement-forge-refiner .gemini/skills/requirement-forge-refiner && 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 "requirement-forge-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/requirement-forge-refiner into .gemini/skills/requirement-forge-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "requirement-forge-refiner", 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 techygarg/lattice requirement-forge-refinerInstalls 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 techygarg/lattice --skill requirement-forge-refiner -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/requirement-forge-refiner .github/skills/requirement-forge-refiner && 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 "requirement-forge-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/requirement-forge-refiner into .github/skills/requirement-forge-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "requirement-forge-refiner", 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 techygarg/lattice --skill requirement-forge-refiner -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install techygarg/lattice requirement-forge-refiner --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techygarg/lattice.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/requirement-forge-refiner .opencode/skills/requirement-forge-refiner && 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 "requirement-forge-refiner" agent skill from https://github.com/techygarg/lattice/tree/main/skills/requirement-forge-refiner into .opencode/skills/requirement-forge-refiner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "requirement-forge-refiner", 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.
requirement-forge-refinerFacilitate a structured conversation to define requirement standards for a project — epic and feature definitions, scenario structure, AC format, priority notation, status workflow, and naming…
Requirement Forge Refiner is an agent skill from techygarg/lattice. Facilitate a structured conversation to define requirement standards for a project — epic and feature definitions, scenario structure, AC format, priority notation, status workflow, and naming conventions. Produces a formal requirement-standards.md that the requirement-quality atom reads via config resolution, customising its embedded defaults for the team's product process. Use when setting up a new project, defining product standards, or when the user says 'set up requirement standards', 'define feature…
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including assets (for example `assets/template.md`).
It sits in Development. The repository describes itself as: Install engineering discipline into any AI coding assistant. Composable skills for design, implementation, review, and team standards. Better process, not just better prompts. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 4d6c35f. 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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
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.
Requirement Forge Refiner loads about 2.9k tokens when it runs. Until then it costs about 164 tokens; SKILL.md has 1,520 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 techygarg/lattice at commit 4d6c35f, republished under its MIT licence (© techygarg). 1,520 words, ~2,936 tokens.
.claude/skills/requirement-forge-refiner/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub..lattice/standards/requirement-standards.md (or custom path from .lattice/config.yaml → paths.requirement_standards)mode: overlay): A slim document containing only sections that differ from the built-in defaults. The requirement-quality atom reads its embedded defaults.md first, then applies this document's sections on top. This is the expected common case.mode: override): A comprehensive standalone document that fully replaces the atom's embedded defaults. For teams whose product process differs fundamentally from the defaults.paths.requirement_standards in .lattice/config.yamlrequirement-quality atom (via config resolution) → requirement-forge molecule (composes the atom)./assets/template.md for the full document structure, default content, and interview guidance commentsThis refiner defines how requirements are structured and expressed for this project. It does not define:
The standards produced here answer: what is an epic, what is a feature, what is a scenario, how are ACs written, how are features named and prioritized. These are the rules the requirement-quality atom enforces — the molecule composes the atom and inherits those rules automatically.
.lattice/config.yaml — check paths.requirement_standards.Before the formal interview, ask:
These two questions are the only free-form listening before the structured interview begins. Synthesize what you hear and carry it forward — do not ask follow-up questions at this stage.
Present the three options:
"How would you like to define your requirement standards?
The built-in defaults cover standard product spec practices well. Option 1 is recommended unless your team's conventions are fundamentally different."
Map the choice:
mode: overlaymode: overrideThis should be fast. Many sections will be "keep as-is."
Every section gets attention and appears in the output.
Read ./assets/template.md and follow the <!-- INTERVIEW GUIDANCE: --> comments for each section. Those comments contain specific questions, probing questions, and what is customizable vs. fixed.
| Decision in | Affects | How |
|---|---|---|
| §2 — Feature size definition | §4 scenario count | Larger features tolerate more scenarios; tighter features need a lower cap |
| §4 — Scenario nomenclature | §8 naming conventions | If "scenario" is renamed, naming conventions must use the new term |
| §4 — Max scenarios per feature | §2 feature definition | These two must be consistent — the split signal in §2 should align with the cap in §4 |
| §5 — AC format | §4 scenario structure | AC format determines what each scenario's criteria look like |
| §6 — Priority notation | feature file frontmatter | Priority field format used in every generated feature file |
| §7 — Status workflow | feature file frontmatter | Status field used in every generated feature file |
| §8 — Naming conventions | all file generation | Feature file names and display names generated by the molecule |
When a dependency is triggered, inform the user: "Since you changed [X], we should also review [Y] — it's affected by that decision."
For each of the 9 default sections:
For each of the 9 default sections:
mode: overlaytemplate.md exactly (the molecule matches sections by heading)mode: overrideStrip all <!-- INTERVIEW GUIDANCE: --> comments from the output. The final document is a clean specification.
Determine output path:
.lattice/config.yaml exists and has paths.requirement_standards, use that path..lattice/standards/requirement-standards.md.Write the document:
.lattice/standards/ directory (and .lattice/ parent) if it does not exist.Update config:
.lattice/config.yaml does not exist, create it with:paths:
requirement_standards: .lattice/standards/requirement-standards.md.lattice/config.yaml exists but has no paths.requirement_standards, add the key. Preserve all existing content.Confirm to user:
"Your requirement standards have been written to [PATH] in [overlay|override] mode. The requirement-forge molecule will now use these standards and will not re-ask structural questions covered here."
Before writing the final document, verify:
template.md exactly<!-- INTERVIEW GUIDANCE: --> comments remainmode: overlay<!-- INTERVIEW GUIDANCE: --> comments remainmode: override.lattice/config.yaml) is correctly updated© techygarg, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (assets) in skills/requirement-forge-refiner of techygarg/lattice.
Open the folder on GitHubat commit 4d6c35f
Requirement Forge Refiner 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 |
|---|---|---|---|---|---|---|
| Requirement Forge Refiner this skilltechygarg/lattice | 199 | — | ~2.9k | Automated safety check: Pass | MIT | |
| Vercel Composition Patternssupabase/supabase | 111k | 58 repos | ~726 | Automated safety check: Pass | MIT | |
| Finishing a Development Branchobra/superpowers | 297k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Typescript Advanced Typesrolling-scopes/rsschool-app | 10k | 25 repos | ~4.2k | Automated safety check: Pass | MPL-2.0 | |
| PR Babysitteropeninterpreter/openinterpreter | 69k | 3 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 5 repos | ~1.1k | Automated safety check: Pass | MIT |
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
rolling-scopes/rsschool-app
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications.
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
onyx-dot-app/onyx
Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments.
techygarg/lattice
Architectural thinking partner for an existing repository — scans the codebase, conducts a structured interview, agrees on current architectural state and recommended direction, and produces a…
techygarg/lattice
Guided setup and upgrade-check experience for Lattice projects -- scans the repository, detects existing configuration and outdated conventions, suggests refiners and available upgrades in priority…
techygarg/lattice
Audit and fix all Lattice documentation, README, docs/, PROJECT.md, GitHub issue templates, and CLAUDE.md to ensure they are fully aligned with the current skill inventory.
techygarg/lattice
Validate any Lattice SKILL.md against all tier conventions — atoms, molecules, and refiners.
techygarg/lattice
Facilitate a structured conversation to define architecture principles for a repository.
techygarg/lattice
Facilitate a structured conversation to define clean code principles for a repository.
Categories
Facilitate a structured conversation to define requirement standards for a project — epic and feature definitions, scenario structure, AC format, priority notation, status workflow, and naming…. Requirement Forge Refiner is an agent skill from techygarg/lattice. Facilitate a structured conversation to define requirement standards for a project — epic and feature definitions, scenario structure, AC format, priority notation, status workflow, and naming conventions.
Requirement Forge Refiner fits situations like: setting up a new project; defining product standards; the user says set up requirement standards; define feature standards.
Run `npx skills add techygarg/lattice --skill requirement-forge-refiner -a claude-code`. Or copy the skill folder (skills/requirement-forge-refiner in techygarg/lattice) into .claude/skills/requirement-forge-refiner in your project. Claude Code loads it when a task matches its description.
Run `npx skills add techygarg/lattice --skill requirement-forge-refiner -a codex`. Or copy the skill folder (skills/requirement-forge-refiner in techygarg/lattice) into .agents/skills/requirement-forge-refiner 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 techygarg/lattice --skill requirement-forge-refiner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/requirement-forge-refiner, .gemini/skills/requirement-forge-refiner, .github/skills/requirement-forge-refiner and .opencode/skills/requirement-forge-refiner in your project.
SKILL.md names no scripts, command-line tools or credentials: Requirement Forge Refiner is instructions for the agent only.
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.
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.
Requirement Forge Refiner is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k 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 Requirement Forge Refiner: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
techygarg (a GitHub user) maintains it in techygarg/lattice, which has 199 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 6, 2026.
Source: techygarg/lattice on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.