Agent skill

Hephaestus Build

by agentlas-ai in agentlas-ai/Agentlas-OS

A skill your agent uses when the user types /prompts:hep-build or /agentlas-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package…

Apache-2.0Auto-check passedAgent Workflows

Install Hephaestus Build

skills CLI
$ npx skills add agentlas-ai/Agentlas-OS --skill hephaestus-build -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install agentlas-ai/Agentlas-OS hephaestus-build --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/agentlas-ai/Agentlas-OS.git skills-src && mkdir -p .claude/skills && cp -r skills-src/codex/plugins/agentlas-core-engine-meta-agent/skills/hephaestus-build .claude/skills/hephaestus-build && rm -rf skills-src

Use ~/.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/

Facts

Skill name
hephaestus-build
GitHub stars
1.6k
Token cost
~2.2k tokens
SKILL.md length
901 words
Files
1
Skills in repo
53
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when the user types /prompts:hep-build or /agentlas-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package…

  • Works in 12 steps: Treat this as the public Codex build… → Resolve the trusted engine root before… → Run the public mode classifier by… → …
  • The user types /prompts:hep-build
  • SKILL.md covers Procedure and Output
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Hephaestus Build is an agent skill from agentlas-ai/Agentlas-OS. Use when the user types /prompts:hep-build or /agentlas-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package an existing local/external agent into Agentlas architecture.

Its SKILL.md is about 2.2k 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 Agent Workflows. The repository describes itself as: Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model. The licence is Apache-2.0.

When your agent uses it

  • The user types /prompts:hep-build
  • /agentlas-build
  • Mentions @Hephaestus for build work
  • Asks to create a single Agentlas agent

Example prompts

  • “/hephaestus-build”

Workflow steps

12 steps, taken from the first numbered list in SKILL.md.

  1. Treat this as the public Codex build surface. Do not expose or ask the user
  2. Resolve the trusted engine root before reading any build contract
  3. Run the public mode classifier by independent ownership boundaries, not by
  4. Run the Builder Interview and Research Gate from
  5. If missing narrow details still change files, adapters, or public/private
  6. Pick one
  7. Load matching support skills.
  8. Write all generated or repaired runtime agent instructions in English
  9. Before writing package files, run
  10. Add the generated command to Claude Code, Codex, Gemini CLI, generic
  11. For team mode, run
  12. Run

What it can do on your machine

Read from SKILL.md and the folder at commit 6254906. 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 (its code samples are bash).

    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

Hephaestus Build loads about 2.2k tokens when it runs. Until then it costs about 64 tokens; SKILL.md has 901 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

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 agentlas-ai/Agentlas-OS at commit 6254906, republished under its Apache-2.0 licence (© agentlas-ai). 901 words, ~2,171 tokens.

Download SKILL.mdSave it as .claude/skills/hephaestus-build/SKILL.md (or your agent's skills folder).
name
hephaestus-build
description
Use when the user types /prompts:hep-build or /agentlas-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package an existing local/external agent into Agentlas architecture.

Hephaestus Build

Procedure

  1. Treat this as the public Codex build surface. Do not expose or ask the user to invoke the older internal support skill names.

  2. Resolve the trusted engine root before reading any build contract:

    bash
    ENGINE=""
    for candidate in \
      "${CODEX_PLUGIN_ROOT:-}" \
      "${CLAUDE_PLUGIN_ROOT:-}" \
      "${PLUGIN_ROOT:-}" \
      "$HOME/.agentlas/runtime/current/host_adapters/codex/plugins/agentlas-core-engine-meta-agent" \
      "$HOME/.agentlas/runtime/current/host_adapters/claude/plugins/agentlas-core-engine-meta-agent" \
      "$HOME/.agentlas/runtime/current" \
      "."
    do
      if [ -n "$candidate" ] && [ -f "$candidate/AGENTS.md" ] && [ -f "$candidate/package-contract.json" ] && [ -f "$candidate/contracts/builder-interview-research-gate.md" ]; then
        ENGINE="$candidate"
        break
      fi
    done
    [ -n "$ENGINE" ] || { echo "Hephaestus engine not found. Run the installer first." >&2; exit 1; }
    RUNNER=""
    for candidate in "$HOME/.agentlas/runtime/current/bin/hephaestus" "$ENGINE/bin/hephaestus"; do
      if [ -x "$candidate" ]; then RUNNER="$candidate"; break; fi
    done
    [ -n "$RUNNER" ] || { echo "Hephaestus runner not found." >&2; exit 1; }

    For an interactive request whose first argument is session, do not resolve a generic PACKAGE_TARGET and do not ask for a JSON/JSONL export. Ask first: "이 세션에서 만든 에이전트를 기본 전역 Agentlas 에이전트 폴더에 만들까요? 다른 위치를 원하면 경로를 알려주세요. 별도 위치를 지정하지 않으면 전역 폴더에 만듭니다." If no alternate location is named, use AGENTLAS_AGENT_HOME or ~/.agentlas/agentlas-agent and create a new safe-slug child package. If a destination is supplied, validate that exact folder. Never overwrite an existing child. The current conversation is the source; do not inspect recent sessions or host databases.

    For every other build request, take exactly one folder explicitly named or confirmed by the user as PACKAGE_TARGET. If none was named, or multiple candidates exist, stop and ask. Never default to ., the cwd, or $ENGINE. Run "$RUNNER" contract resolve-target "$PACKAGE_TARGET" --base "$PWD" and set PACKAGE_ROOT only to the status-ok receipt's exact package_root. Nonzero or error receipts are blockers.

    Read $ENGINE/AGENTS.md, $ENGINE/.agentlas/mode-map.json, the selected mode contract under $ENGINE/modes/, and $ENGINE/contracts/builder-interview-research-gate.md. Do not substitute files from the user's package workspace.

  3. Run the public mode classifier by independent ownership boundaries, not by keywords such as "team":

    • package or repair existing material -> 30-agentlas-packager;
    • current interactive conversation invoked with session, or an explicitly exported session in a terminal/headless run -> 40-session-agent-builder;
    • one independently owned context/tools/success standard -> 10-single-agent-builder;
    • two or more roles with separate context, permissions, success standards, handoff, or synthesis needs -> 20-multi-agent-team-builder. If the shape is unclear, ask before generating. The user-facing question must be plain language, for example: "이 일을 한 명의 전문가가 처음부터 끝까지 맡으면 되나요, 아니면 조사/분석/검토처럼 여러 전문가가 나눠 맡고 마지막에 합쳐야 하나요?" Do not expose internal labels such as single-agent, team-builder, ownership boundary, memory/context, synthesis, or produces/consumes.
  4. Run the Builder Interview and Research Gate from $ENGINE/contracts/builder-interview-research-gate.md before writing substantial package files:

    • for an interactive session request, treat the current conversation as the source interview and ask only the destination question plus focused gaps that would change scope, permissions, output, or safety;
    • for other builds, ask an 8-12 question first batch when the request is vague;
    • continue follow-ups until target user, tasks, inputs, outputs, examples, role count, separated tools or permissions, final merge needs, execution order, memory, failure modes, and evals are clear;
    • phrase shape questions in everyday language. Ask who handles which part, whether each role needs different files/accounts/tools, whether someone must merge the result, and whether work can run at the same time or must pass from one person to the next;
    • research official or primary docs, similar agent repositories or comparables, GitHub examples, academic/professional theory, and tool/plugin docs;
    • compare selected and rejected tools/plugins with permission, secret, fallback, and smoke-test notes;
    • synthesize domain-expert behavior from interview answers, comparable agents/repos, theory, and tool choices;
    • write docs/builder-interview.md, docs/research-sources.md, docs/tool-selection.md, docs/domain-expert-synthesis.md, docs/prompt-performance-contract.md, and .agentlas/capability-eval-plan.json.
  5. If missing narrow details still change files, adapters, or public/private boundaries, ask one to five clarify questions before generating.

  6. Pick one:

    • 10-single-agent-builder;
    • 20-multi-agent-team-builder;
    • 30-agentlas-packager;
    • 40-session-agent-builder. For 40-session-agent-builder, run the current-session two-pass flow: first show a Generalized Session Report that extracts reusable intent, procedures, corrections, failed approaches, validation, and conditional IF / THEN / BECAUSE / AVOID / INSTEAD rules; then offer Build Agent or Edit. Only the approved report is converted into the standalone agent prompt and package. Do not present JSON/JSONL as an interactive input.
  7. Load matching support skills.

  8. Write all generated or repaired runtime agent instructions in English: AGENTS.md, CLAUDE.md, GEMINI.md, agent.md, skills, workflow/command adapters, runtime prompts, handoff contracts, return contracts, and operating docs. Translate Korean or other-language source material into English agent behavior. Localized public copy, routing trigger examples, and sample user inputs may use the target user language.

  9. Before writing package files, run "$RUNNER" contract scaffold "$PACKAGE_ROOT" --mode <single|team|package>. After the routing card is authored, run "$RUNNER" contract complete "$PACKAGE_ROOT" --mode <single|team|package>. Emit or repair Agentlas contracts, including .agentlas activation seed files and .agentlas/global-commands.json when local continuity is part of the output.

  10. Add the generated command to Claude Code, Codex, Gemini CLI, generic AGENTS.md, and terminal adapters. For teams, expose the orchestrator/HQ command and route workers through HQ unless direct worker commands were requested.

  11. For team mode, run "$ENGINE/scripts/verify-team-package.sh" "$PACKAGE_ROOT" when that focused gate exists. If it fails, do not report completion; collapse the output to a single-agent package or add the required orchestrator/HQ and team contracts.

  12. Run "$RUNNER" contract verify "$PACKAGE_ROOT" --mode <single|team|package>. A non-zero exit or non-empty blocker list means blocked, never completed. Do not use the engine repository's scripts/verify-package.sh as generated-package evidence; that script verifies the engine repository itself.

  13. Once verification and local registration have succeeded, ask one final two-choice storage question using structured controls when available: Cloud에 올리기 or 로컬에만 저장. Cloud means owner-private Agent Cloud storage, restorable on another signed-in Desktop. Mobile can use the package only after a paired Desktop restores/installs it; Cloud is not a hosted LLM runtime. Local-only performs no network mutation.

  14. Never upload by default. Missing input and non-interactive execution are local-only. Only after explicit Cloud consent, run the trusted Hephaestus runner with upload <exact-verified-package-root> --visibility private-link. Keep the local package on every auth/offline/CAS/quota/scan failure and report an exact retry command. Public Hub publication remains a separate explicit action.

Show full SKILL.md (9 more words)Show less

Output

Return status, evidence, output, global_commands, interview_research, and blockers.

© agentlas-ai, Apache-2.0. 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 codex/plugins/agentlas-core-engine-meta-agent/skills/hephaestus-build of agentlas-ai/Agentlas-OS.

Open the folder on GitHubat commit 6254906

Compare with similar skills

Hephaestus Build 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.

Hephaestus Build compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Hephaestus Build this skillagentlas-ai/Agentlas-OS1.6k—~2.2kAutomated safety check: PassApache-2.0
MCP Server Builderanthropics/skills180k63 repos~2.3kAutomated safety check: PassApache-2.0
Hook Development for Claude Code Pluginsanthropics/claude-plugins-official38k10 repos~4.1kAutomated safety check: NotesApache-2.0
Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
Executing Plans Inlineobra/superpowers297k2 repos~5.1kAutomated safety check: PassMIT
Skill CreatorAzure/azqr79589 repos~8.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Hephaestus Build

What does Hephaestus Build do?

A skill your agent uses when the user types /prompts:hep-build or /agentlas-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package…. Hephaestus Build is an agent skill from agentlas-ai/Agentlas-OS. Use when the user types /prompts:hep-build or /agentlas-build, mentions @Hephaestus for build work, asks to create a single Agentlas agent, create a multi-agent team, or package an existing local/external agent into Agentlas architecture.

When should I use Hephaestus Build?

Hephaestus Build fits situations like: the user types /prompts:hep-build; /agentlas-build; mentions @Hephaestus for build work; asks to create a single Agentlas agent.

How do I install Hephaestus Build in Claude Code?

Run `npx skills add agentlas-ai/Agentlas-OS --skill hephaestus-build -a claude-code`. Or copy the skill folder (codex/plugins/agentlas-core-engine-meta-agent/skills/hephaestus-build in agentlas-ai/Agentlas-OS) into .claude/skills/hephaestus-build in your project. Claude Code loads it when a task matches its description.

How do I install Hephaestus Build in Codex?

Run `npx skills add agentlas-ai/Agentlas-OS --skill hephaestus-build -a codex`. Or copy the skill folder (codex/plugins/agentlas-core-engine-meta-agent/skills/hephaestus-build in agentlas-ai/Agentlas-OS) into .agents/skills/hephaestus-build in your project. Codex loads it when a task matches its description.

Can I use Hephaestus Build 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 agentlas-ai/Agentlas-OS --skill hephaestus-build -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hephaestus-build, .gemini/skills/hephaestus-build, .github/skills/hephaestus-build and .opencode/skills/hephaestus-build in your project.

What does Hephaestus Build need to run?

SKILL.md names no scripts, command-line tools or credentials: Hephaestus Build is instructions for the agent only.

Does Hephaestus Build 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 Hephaestus Build 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 Hephaestus Build use?

Hephaestus Build is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hephaestus Build use?

About 2.2k tokens (SKILL.md is roughly 8.7k 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 Hephaestus Build?

Skills that share tags, products or a category with Hephaestus Build: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hephaestus Build?

agentlas-ai (a GitHub organization) maintains it in agentlas-ai/Agentlas-OS, which has 1,582 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on October 8, 2026.

Source: agentlas-ai/Agentlas-OS on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.