hep-network

SkillProductivity

Staff a task from registered Local, owner Cloud, and public Hub agents.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the hep-network skill

What this skill tells your AI

The instructions your AI receives, as published by agentlas-ai/agentlas-os in kimi/skills/hep-network/SKILL.md and read by ahel’s review.

Update fallback: 자동 업데이트가 안 되면 hephaestus update를 한 번 실행하세요. 업데이트하지 않아도 현재 버전 명령은 그대로 동작합니다.

Hephaestus Workforce Network

Raw request: $ARGUMENTS

Act as the active top-level workforce orchestrator. Use MCP server hephaestus-network, the local Agentlas OS Core and only host-visible Workforce MCP. Core reaches Cloud and Hub through its internal upstream client. Network means registered Local + signed-in owner Cloud + public Hub.

The user does not need to say goal. First read workforce.goal_context(projectDir) and reuse an active binding for the same ongoing work before considering recruitment.

Before the first Cloud or Hub source call, reuse the installed Agentlas sign-in. Resolve the runner only for authentication; staffing remains in the Workforce MCP tools:

RUNNER=""
for candidate in \
  "$HOME/.agentlas/runtime/current/bin/hephaestus" \
  "./bin/hephaestus"
do
  if [ -n "$candidate" ] && [ -x "$candidate" ]; then RUNNER="$candidate"; break; fi
done
[ -n "$RUNNER" ] && "$RUNNER" auth ensure --timeout 180 >/dev/null 2>&1 || true
  1. Author a redacted agentlas.workforce-work-order.v1 with substantive role slots. Fill a slot with task/cardinality/criticality plus only the communities/skills/knowledge, runtimes, and languages that genuinely constrain the hire; omit every other list field (absent = empty — the wire normalizes) and never fill requiredToolCapabilities, requiredAuthorities, forbiddenAuthorities, consumes, produces, requiredRoles, or modalities: tools, authorities, and modalities attach to the executing runtime, not the agent card, so those gates only exclude real candidates — put ordinary inputs/outputs in the task text and handoffs in edges. Private grounding stays local. Write every discovery-facing field in English, faithfully translating a non-English request (the candidate corpus is English and cross-lingual matching buries the correct agent — measured 1st vs 144th for one query); keep an untranslatable term with a short English gloss. languages is the delivery language, not the search language — keep it as the required output language even though the order is authored in English.
  2. Call workforce.search_candidates with {workOrder, sourceScope: "network"} and preserve source receipts plus selectionSessionId. The default response is a projected menu, not a complete federationResult; do not echo it as one. Unavailable sources remain explicit.
  3. From content and qualification evidence, author agentlas.workforce-selection.v1 yourself. Call workforce.validate_selection with {workOrder, selection} and keep its response as federatedSelection. Revise on rejection. Deterministic code may enforce governance but may not pick, rerank, or silently substitute.
  4. Call workforce.prepare_execution with {workOrder, selection, federatedSelection, projectDir, goalId?} and require exact source, release, package/content, runtime-bundle, permission, and context pins for every selected row. projectDir is mandatory; pass the incumbent goalId when continuing. Otherwise Core derives it from the WorkOrder id and automatically binds the successful plan before execution.
  5. Every later turn reads workforce.goal_context, reuses the incumbent roster plus local skills when sufficient, and recruits only a real additive gap using the same goalId. Record the turn posture through workforce.record_goal_turn.
  6. Before every bound invocation, advertise the live host sessions and call model.resolve_allocation with that inventory plus the host-owned stage: planner/manager-plan, worker, manager-synthesis/synthesis, or verifier. Use the receipt's exact provider, model, and effort for that invocation. Model pins and ceilings come only from the MCP server's operator policy, never from the task or tool arguments. A missing worker policy inherits orchestrator; orchestrator never falls through to worker.
  7. Spawn only the useful bound planner/manager, worker, synthesis, and verifier invocations with explicit artifact handoffs; preserve authoritative Team graphs. Allocation receipts have usage: null before execution, so record actual usage on the later invocation/run receipt instead of inventing zero.

Keep the roster bound across turns, sessions, runtime restarts, and context compaction until explicit whole-goal completion/cancellation via workforce.complete_goal(explicitCompletion=true). Lease expiry affects only the next Hub charge; it never dismisses the roster. Standby is durable availability, not a continuously running model. Memory/Experience accrue on actual invocations.

Report executed only from a receipt proving every child invocation, handoff, synthesis, and a passing independent verifier. Otherwise report the last truthful state. Do not call legacy hephaestus_route, bypass Core with direct remote search, or use popularity/history/price/availability as semantic fit. Exact duplicate releases collapse Local > Cloud > Hub only with verified identical lineage.

Signals

GitHub stars
1k
Forks
103
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
hep-network
Source
github.com/agentlas-ai/agentlas-os