Hephaestus build
Skill agentlas-ai/Agentlas-OS/codex/plugins/agentlas-core-engine-meta-agent/skills/hephaestus-build
Use when the user types /prompts:hep-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.From its SKILL.md
npx -y skills add agentlas-ai/Agentlas-OS --skill hephaestus-buildAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- runs commandsInstructs the agent to run 3 commands, including `scripts/verify-team-package.sh <generated-package-root>` and 2 more.
SKILL.md
5.0 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
Hephaestus Build
Procedure
- Treat this as the public Codex build surface. Do not expose or ask the user to invoke the older internal support skill names.
- Read
AGENTS.mdand.agentlas/mode-map.jsonwhen they exist in the current workspace. - Run the public mode classifier by independent ownership boundaries, not by
keywords such as "team":
- package or repair existing material ->
30-agentlas-packager; - 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 assingle-agent,team-builder, ownership boundary, memory/context, synthesis, or produces/consumes.
- package or repair existing material ->
- Run the Builder Interview and Research Gate from
docs/builder-interview-research-gate.mdbefore writing substantial package files:- 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.
- If missing narrow details still change files, adapters, or public/private boundaries, ask one to five clarify questions before generating.
- Pick one:
10-single-agent-builder;20-multi-agent-team-builder;30-agentlas-packager.
- Load matching support skills.
- 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. - Emit or repair Agentlas contracts, including
.agentlasactivation seed files and.agentlas/global-commands.jsonwhen local continuity is part of the output. - 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.
- Run
scripts/verify-team-package.sh <generated-package-root>for generated or repaired packages. If it fails, do not report completion; collapse the output to a single-agent package or add the required orchestrator/HQ and team contracts. - Verify with
scripts/verify-package.sh. - 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.
- 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.
Output
Return status, evidence, output, global_commands, interview_research,
and blockers.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.