Nerdzao Elite
aiskillstore/marketplace
Senior Elite Software Engineer (15+) and Senior Product Designer.
Generate implementation code from an approved design blueprint or verbal requirements.
$ npx skills add techygarg/lattice --skill code-forge -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install techygarg/lattice code-forge --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/code-forge .claude/skills/code-forge && 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 "code-forge" agent skill from https://github.com/techygarg/lattice/tree/main/skills/code-forge into .claude/skills/code-forge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-forge", 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/code-forgeType 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 code-forge -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install techygarg/lattice code-forge --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/code-forge .agents/skills/code-forge && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "code-forge" agent skill from https://github.com/techygarg/lattice/tree/main/skills/code-forge into .agents/skills/code-forge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-forge", 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 code-forge -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install techygarg/lattice code-forge --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/code-forge .cursor/skills/code-forge && 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 "code-forge" agent skill from https://github.com/techygarg/lattice/tree/main/skills/code-forge into .cursor/skills/code-forge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-forge", 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/code-forge--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 code-forge -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install techygarg/lattice code-forge --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/code-forge .gemini/skills/code-forge && 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 "code-forge" agent skill from https://github.com/techygarg/lattice/tree/main/skills/code-forge into .gemini/skills/code-forge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-forge", 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 code-forgeInstalls 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 code-forge -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/code-forge .github/skills/code-forge && 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 "code-forge" agent skill from https://github.com/techygarg/lattice/tree/main/skills/code-forge into .github/skills/code-forge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-forge", 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 code-forge -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 code-forge --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/code-forge .opencode/skills/code-forge && 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 "code-forge" agent skill from https://github.com/techygarg/lattice/tree/main/skills/code-forge into .opencode/skills/code-forge/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-forge", 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.
code-forgeGenerate implementation code from an approved design blueprint or verbal requirements.
Code Forge is an agent skill from techygarg/lattice. Generate implementation code from an approved design blueprint or verbal requirements. Composes context anchoring, architecture, clean code, DDD, security, and test quality into an inside-out implementation workflow. Use when moving from design to code, implementing approved contracts, or when the user says 'implement', 'code this', 'build it', 'forge the code', or 'generate the code'.
Its SKILL.md is about 3.1k 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 Domain-driven design, Code quality and Design to code. 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.
5 steps, taken from the step headings 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.
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.
Code Forge loads about 3.1k tokens when it runs. Until then it costs about 100 tokens; SKILL.md has 1,560 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). 1,560 words, ~3,081 tokens.
.claude/skills/code-forge/SKILL.md (or your agent's skills folder).Read and apply:
framework:knowledge-priming -- Load project context (stack, architecture, conventions) so implementation matches the real project. (always)framework:context-anchoring -- Find and load the feature's context anchor doc; enrich it as implementation decisions are made (Create / Load / Enrich behaviors). (always)framework:learning-harvest -- Load prior operational learnings to inform implementation at session start; harvest new ones at session end. (always)framework:collaborative-judgment -- Surface genuine judgment calls as structured options instead of silently assuming. (always)framework:architecture -- Layer placement, dependency direction, structural validation. (always)framework:clean-code -- Craft guardrails: SRP, naming, complexity, error handling. (always)framework:domain-driven-design -- Aggregates, entities, value objects, domain services. (conditional: domain-layer components only)framework:secure-coding -- Trust bounds, injection prevention, secrets handling. (conditional: trust-boundary code only)framework:test-quality -- AAA structure, isolation, assertion quality, naming. (always when writing tests)framework:learning-harvest Load behavior. Focus hint: "implementation session — focus: implementation craft, quality signals, reliability".framework:context-anchoring Document Discovery: scan the context base directory (per the atom's Config Resolution) for an existing anchor doc covering this feature's implementation.Design completeness check — run both gates before Step 2 (no context doc exists → skip both, proceed as "Without approved design"):
Check 1 — status: Read the context doc frontmatter status.
approved → pass.complete → this feature was already implemented. If the current request is new scope, recommend /design-blueprint for a fresh design pass; if the user confirms proceeding on the existing design, continue as "With approved design" (Check 2 still applies).draft or a missing field) → STOP: "Context doc not approved (status: [value]). Run /design-blueprint first. Proceed anyway?" On confirmation → log it in the Decisions Log and continue as "Without approved design".Check 2 — levels present: Scan the body for ## Design: Level 3 and ## Design: Level 4.
Both pass → proceed as "With approved design".
With approved design: extract the component list and layer assignments from the context anchor doc. Use the Level 2 (Components) decisions for layer placement and Level 3 (Interactions) for dependency flow.
Without approved design: classify the required components into architecture layers using the layer definitions from framework:architecture. For each component determine:
If framework:architecture resolved no layer definitions (neither defaults nor a custom doc), surface it: "No architecture rules available. Run /architecture-refiner to define your architecture standards. Proceeding without architecture guidance." Continue with the remaining atom rails.
Present the proposed layer assignments to the user for approval before proceeding.
In both cases, plan an inside-out implementation order following the dependency direction from the loaded architecture doc — start at the innermost layer (no outward dependencies) and work outward, so each layer's dependencies already exist when it is built.
Classify each operation per the flow patterns in the loaded architecture doc (e.g., command vs query flows, or the equivalent distinction in your architecture style).
Present the implementation plan — ordered component list, layer assignments, flow classifications — and confirm with the user before writing code. If the user rejects or corrects the plan, revise and re-present it. STOP: Never start coding on an unagreed plan.
After the plan is approved, ask the user to choose a review mode:
"How should we review the implementation?"
- Layer-by-layer (recommended) — implement each layer fully, pause for review before the next. One review point per layer.
- Full autonomy — implement everything end-to-end, present the complete result. One review point at the end. (If a blueprint exists, still pause on any deviation from the approved design.)
- Component-by-component — pause after each individual component for feedback. Maximum review points.
Default to layer-by-layer if the user expresses no preference.
For each component in planned order, generate code and tests together — tests are not an afterthought.
Every component:
framework:architecture; dependency direction follows the loaded architecture rules.framework:clean-code self-validation during generation. Inline checks: SRP compliance, meaningful naming, low cyclomatic complexity, proper error handling, no magic values, clean function signatures, no dead code, appropriate abstraction level, clear control flow, minimal comments (the code documents itself).framework:test-quality self-validation.Conditional checks per component:
framework:domain-driven-design self-validation.framework:secure-coding self-validation.Post-generation verification (every component, all review modes):
After generating each component, before presenting it to the user:
framework:collaborative-judgment protocol before showing code. Never silently resolve.Pacing — follow the user's chosen review mode:
These checks verify architecture coherence, not code quality (already verified per-component in Step 3). After all components are implemented:
framework:architecture verification across all components — inter-component dependency direction follows the loaded architecture rules; no layer imports from a layer it is not permitted to depend on.framework:secure-coding across component boundaries — data flowing between components crosses trust bounds safely.Throughout Steps 3-4, use framework:context-anchoring Enrich behavior to keep the living doc current:
Harvest learnings: run framework:learning-harvest Harvest behavior. Session context: "implementation session — code generation from design contracts". Synthesize and propose cross-cutting patterns from this session — implementation gotchas, design-to-reality gaps, library/framework lessons. The user confirms what enters the document. STOP: run this before closing the feature lifecycle below.
Close the feature lifecycle: write status: complete into the context doc frontmatter. STOP: required discrete file edit.
STOP: do not write status to requirement_doc. The requirement's status belongs to whoever manages it — a human, or an external system it may live in. This molecule manages only its own context doc.
After enriching the context doc, recommend review:
"Implementation complete. Recommend running
/reviewon the generated code before considering the feature done — it provides an independent quality assessment against the same atom standards, catches issues the generator may be blind to, and captures learnings for future sessions."
© techygarg, MIT. 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 skills/code-forge of techygarg/lattice.
Open the folder on GitHubat commit 4d6c35f
Code Forge 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 |
|---|---|---|---|---|---|---|
| Code Forge this skilltechygarg/lattice | 198 | — | ~3.1k | Automated safety check: Pass | MIT | |
| Nerdzao Eliteaiskillstore/marketplace | 430 | 4 repos | ~443 | Automated safety check: Pass | None | |
| Brooks Reviewhyhmrright/brooks-lint | 1.5k | 1 repos | ~430 | Automated safety check: Pass | MIT | |
| Dotnet Csharpnovotnyllc/dotnet-artisan | 233 | — | ~1.7k | Automated safety check: Pass | MIT | |
| 111 Java Maven Dependenciesjabrena/plinth | 445 | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Clean Architecturewondelai/skills | 2.4k | — | ~4.1k | Automated safety check: Pass | MIT |
aiskillstore/marketplace
Senior Elite Software Engineer (15+) and Senior Product Designer.
hyhmrright/brooks-lint
PR code review that surfaces decay risks, design smells, and maintainability issues with concrete Symptom → Source → Consequence → Remedy findings, drawing on twelve classic engineering books.
novotnyllc/dotnet-artisan
Baseline C skill loaded for every .NET code path. An agent skill from novotnyllc/dotnet-artisan.
jabrena/plinth
A skill your agent uses when you need to add or evaluate Maven dependencies that improve code quality or domain modeling — including nullness annotations (JSpecify), static analysis (Error Prone +…
wondelai/skills
Structure software around the Dependency Rule: source code dependencies point inward from frameworks to use cases to entities.
wondelai/skills
Guided journey from a raw app idea to a validated, cleanly architected first version that ships on a sustainable cadence.
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
Generate implementation code from an approved design blueprint or verbal requirements. Code Forge is an agent skill from techygarg/lattice. Generate implementation code from an approved design blueprint or verbal requirements.
Code Forge fits situations like: moving from design to code; implementing approved contracts; the user says implement; generate the code.
Run `npx skills add techygarg/lattice --skill code-forge -a claude-code`. Or copy the skill folder (skills/code-forge in techygarg/lattice) into .claude/skills/code-forge in your project. Claude Code loads it when a task matches its description.
Run `npx skills add techygarg/lattice --skill code-forge -a codex`. Or copy the skill folder (skills/code-forge in techygarg/lattice) into .agents/skills/code-forge 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 code-forge -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-forge, .gemini/skills/code-forge, .github/skills/code-forge and .opencode/skills/code-forge in your project.
SKILL.md names no scripts, command-line tools or credentials: Code Forge 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.
Code Forge is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.1k 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 Code Forge: Nerdzao Elite (aiskillstore/marketplace, 430 stars), Brooks Review (hyhmrright/brooks-lint, 1.5k stars), Dotnet Csharp (novotnyllc/dotnet-artisan, 233 stars) and 111 Java Maven Dependencies (jabrena/plinth, 445 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 198 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.