/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.
$ npx -y skills add agentlas-ai/Agentlas-OS --skill hephaestus-build --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/hephaestus-build
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
hephaestus-build.SKILL.mdname: hephaestus-build
description: "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."
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. Read `AGENTS.md` and `.agentlas/mode-map.json` when they exist in the current 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`;
- 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 `docs/builder-interview-research-gate.md` before 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`. 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`.
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. 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. 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. 12. Verify with `scripts/verify-package.sh`. 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.
Output
Return `status`, `evidence`, `output`, `global_commands`, `interview_research`, and `blockers`.
Read more
name: hephaestus-build description: "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."
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. Read `AGENTS.md` and `.agentlas/mode-map.json` when they exist in the current 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`;
- 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 `docs/builder-interview-research-gate.md` before 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`. 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`.
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. 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. 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. 12. Verify with `scripts/verify-package.sh`. 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.
Output
Return `status`, `evidence`, `output`, `global_commands`, `interview_research`, and `blockers`.
Agent OS: keep specialist agents in a hub, spin up a temporary orchestrator per task. Local-first, works with any model.
Other skills on agentlas-os.
- /agentlas-core-engine-meta-agent
Use when creating a single Agentlas agent, creating a multi-agent team, or packaging an existing local/external agent into Agentlas architecture. Make sure to use this for /meta-agent requests.
Open skill - /hephaestus-cloud
Use when the user types /hep-cloud or asks to staff from THEIR OWN Agentlas cloud packages only. Cloud is one exact source scope; Network means Local + owner Cloud + public Hub.
Open skill - /hephaestus-network
Use when the user types $hephaestus-network or /hep-network, mentions @Hephaestus, or asks Agentlas to staff a durable goal from registered Local, owner Cloud, and public Hub agents or teams. The active host LLM staffs each turn; the exact roster remains goal-bound until
Open skill - /hephaestus-storm
Use when the user types /hep-storm, says @Hephaestus storm <goal>, or asks to drive a goal to verified completion through a force-robust Stormbreaker loop. Stormbreaker routes the goal to real Agentlas specialists, materializes a dependency-ordered pipeline fabric, and runs each
Open skill - /hephaestus-upload
Use when the user types $hephaestus-upload or /hep-upload, or asks to upload, publish, or list an Agentlas agent or team. Ask Cloud (private) vs Agentlas Hub (public) FIRST, then publish through the bundled Hephaestus gate.
Open skill - /routing-card-authoring
Use whenever a build emits or repairs .agentlas/routing-card.json — the shared card contract for the single-agent builder, the team builder, and the packager. States what belongs in every field, which fields the hub can actually match on, and which fields silently break matching
Open skill

