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Enrich boardroom agent JSON-LD state files with legend-derived domain knowledge, skills, persona, and language from the boardroom-agents spec
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Based on SOC occupation classification
Enrich CEO (Steve Jobs) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec
Enrich CFO (Warren Buffett) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec
Enrich CHRO (Peter Drucker) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec
Enrich CMO (Seth Godin) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec
Enrich COO (W. Edwards Deming) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec
Enrich CSO (Sun Tzu) boardroom agent JSON-LD state file with legend-derived context enrichment from the boardroom-agents spec
| name | boardroom-agent-state |
| description | Enrich boardroom agent JSON-LD state files with legend-derived domain knowledge, skills, persona, and language from the boardroom-agents spec |
| license | MIT |
| metadata | {"author":"ASISaga","version":"2.0","category":"boardroom","role":"agent-state-specialist"} |
| allowed-tools | Bash(python:*) Read Edit |
Role: Boardroom Agent State Enrichment Specialist
Scope: boardroom/mind/*/Manas/ — agent Manas (memory) and boardroom/mind/*/Buddhi/ — agent Buddhi (intellect)
Version: 2.0
Orchestrate context enrichment across all boardroom agents. Each agent has a dedicated skill
that contains the precise legend-derived domain_knowledge, skills, persona, and language
values for that agent. Use this skill as the entry point to discover the right agent skill,
or for cross-agent operations such as full-roster validation.
| Role | Legend | Manas file | Dedicated skill |
|---|---|---|---|
| CEO | Steve Jobs | boardroom/mind/ceo/Manas/ceo.jsonld | .github/skills/boardroom-agent-state-ceo/SKILL.md |
| CFO | Warren Buffett | boardroom/mind/cfo/Manas/cfo.jsonld | .github/skills/boardroom-agent-state-cfo/SKILL.md |
| COO | W. Edwards Deming | boardroom/mind/coo/Manas/coo.jsonld | .github/skills/boardroom-agent-state-coo/SKILL.md |
| CMO | Seth Godin | boardroom/mind/cmo/Manas/cmo.jsonld | .github/skills/boardroom-agent-state-cmo/SKILL.md |
| CHRO | Peter Drucker | boardroom/mind/chro/Manas/chro.jsonld | .github/skills/boardroom-agent-state-chro/SKILL.md |
| CTO | Alan Turing | boardroom/mind/cto/Manas/cto.jsonld | .github/skills/boardroom-agent-state-cto/SKILL.md |
| CSO | Sun Tzu | boardroom/mind/cso/Manas/cso.jsonl ¹ | .github/skills/boardroom-agent-state-cso/SKILL.md |
| Founder | Paul Graham | boardroom/mind/founder/Manas/founder.jsonld | .github/skills/boardroom-agent-state-founder/SKILL.md |
¹ The CSO agent uses
.jsonl(newline-delimited JSON) rather than.jsonld.
The context object is immutable (read-only by BoardroomStateManager). Required fields:
| Field | Constraint |
|---|---|
name | Legend's full name (string) |
fixed_mandate | Domain mandate (matches CXO_DOMAINS[id]["domain"]) |
core_logic | Defining maxim — 1–3 sentences from the legend |
immutable_constraints | List of 3 read-only guiding principles |
Enrichment fields (optional per schema validator, required per this spec):
| Field | Constraint |
|---|---|
domain_knowledge | List of 4–5 deep expertise areas |
skills | List of 4–5 concrete capabilities |
persona | 2–4 sentence identity description |
language | 2–3 sentence vocabulary/style description |
The content.company_state and content.product_state objects are validated by
BoardroomStateManager against _AGENT_PERSPECTIVE_KEYS and require:
entity_id, entity_name, perspective, domain_knowledge, skills, persona,
language, software_interfaces, current_signals
→ See src/business_infinity/boardroom.py → BoardroomStateManager._AGENT_PERSPECTIVE_KEYS
# Validate all agent states and Buddhi files load correctly
PYTHONPATH=/tmp/aos_mock:src python3 -m pytest tests/ -q -k "boardroom"
# Spot-check context enrichment and Buddhi completeness across all agents
PYTHONPATH=/tmp/aos_mock:src python3 - <<'PY'
from business_infinity.boardroom import BoardroomStateManager
for agent_id in BoardroomStateManager.get_registered_agent_ids():
ctx = BoardroomStateManager.load_agent_context(agent_id)
for field in ("domain_knowledge", "skills", "persona", "language"):
assert field in ctx, f"{agent_id} context missing '{field}'"
buddhi = BoardroomStateManager.load_agent_buddhi(agent_id)
assert buddhi["agent_id"] == agent_id
print(f"✓ {agent_id}: {ctx['name']} — Manas and Buddhi OK")
PY
# Run all tests
PYTHONPATH=/tmp/aos_mock:src python3 -m pytest tests/ -q
# Lint boardroom module
PYTHONPATH=/tmp/aos_mock:src python3 -m pylint src/business_infinity/boardroom.py --disable=C0114,C0115,C0116,E0401
→ Spec: .github/specs/boardroom-agents.md — Legend archetypes, domain knowledge, and JSON-LD schema
→ State manager: src/business_infinity/boardroom.py → BoardroomStateManager
→ Manas files: boardroom/mind/*/Manas/
→ Buddhi files: boardroom/mind/*/Buddhi/buddhi.jsonld
→ Shared state: boardroom/state/ — collective boardroom state
→ MVP spec: .github/specs/mvp.md — C-suite agent roster
→ Repository spec: .github/specs/repository.md
Version: 3.0 — Updated to mind/Manas/Buddhi architecture
Last Updated: 2026-04-03