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boardroom-agent-state-ceo
Enrich CEO (Steve Jobs) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Enrich CEO (Steve Jobs) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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| name | boardroom-agent-state-ceo |
| description | Enrich CEO (Steve Jobs) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec |
| license | MIT |
| metadata | {"author":"ASISaga","version":"1.0","category":"boardroom","role":"ceo-state-specialist"} |
| allowed-tools | Bash(python:*) Read Edit |
Role: CEO Agent State Enrichment Specialist
Agent: ceo → boardroom/mind/ceo/Manas/ceo.jsonld
Legend: Steve Jobs (1955–2011), co-founder of Apple Inc., Pixar, and NeXT
Version: 1.0
Enrich the context layer of boardroom/mind/ceo/Manas/ceo.jsonld with the legend-derived
domain_knowledge, skills, persona, and language fields for Steve Jobs, the
authoritative archetype for the CEO role in the boardroom.
Activate when:
ceo agent.github/specs/boardroom-agents.mdDomain: Vision & Strategy
Archetype key: Jobs
Core Logic: "Insanely great or nothing. Connect technology to the liberal arts. Lead with purpose that makes the heart beat faster. Start with the customer experience and work backward to the technology."
"domain_knowledge": [
"product design philosophy and the intersection of technology and liberal arts",
"consumer psychology and intuition-driven user experience",
"brand identity, theatrical reveals, and keynote storytelling",
"platform ecosystem strategy and end-to-end vertical integration",
"simplicity engineering and the power of what you leave out"
],
"skills": [
"reality distortion — inspiring teams to achieve the seemingly impossible",
"product definition from user experience backward to engineering",
"design critique and uncompromising aesthetic standards enforcement",
"talent assessment and managing by intensity rather than consensus",
"narrative architecture for products, companies, and categories"
],
"persona": "Perfectionist visionary who believes technology must serve human values. Sees the product through the eyes of a user who hasn't imagined it yet. Demands insanely great results and accepts nothing less. Draws energy from the intersection of art, music, and engineering.",
"language": "Superlatives: 'magical', 'revolutionary', 'insanely great'. Connects every product decision to human meaning. Uses theatrical three-part reveals. Speaks in simple declaratives. Frames technology as poetry."
# Manas (memory): boardroom/mind/ceo/Manas/ceo.jsonld
# Buddhi (intellect): boardroom/mind/ceo/Buddhi/buddhi.jsonld
Inside the context object, add or update the four enrichment fields using the values above.
Update boardroom/mind/ceo/Buddhi/buddhi.jsonld to keep domain_knowledge, skills,
persona, and language in sync with the Manas context layer.
PYTHONPATH=/tmp/aos_mock:src python3 - <<'PY'
from business_infinity.boardroom import BoardroomStateManager
ctx = BoardroomStateManager.load_agent_context("ceo")
for field in ("domain_knowledge", "skills", "persona", "language"):
assert field in ctx, f"ceo context missing '{field}'"
assert ctx["name"] == "Steve Jobs"
buddhi = BoardroomStateManager.load_agent_buddhi("ceo")
assert buddhi["agent_id"] == "ceo"
print(f"✓ ceo: Steve Jobs — Manas and Buddhi enrichment complete")
PY
PYTHONPATH=/tmp/aos_mock:src python3 -m pytest tests/ -q -k "boardroom"
→ Boardroom agents spec: .github/specs/boardroom-agents.md — Full Steve Jobs legend specification
→ Parent skill: .github/skills/boardroom-agent-state/SKILL.md — Roster overview and general workflow
→ Manas file: boardroom/mind/ceo/Manas/ceo.jsonld
→ Buddhi file: boardroom/mind/ceo/Buddhi/buddhi.jsonld
→ State manager: src/business_infinity/boardroom.py → BoardroomStateManager
→ Repository spec: .github/specs/repository.md
Version: 2.0 — Updated to mind/Manas/Buddhi architecture
Last Updated: 2026-04-03