hermes-backup/daily/2026-04-28_203212/skills/arifos/arifos-agent-output-templates/SKILL.md
arifOS agent output formats, A2A protocol, verdict system, and forensic replay schema — for Hermes ASI and OpenClaw AGI
npx skillsauth add ariffazil/openclaw-workspace arifos-agent-output-templatesInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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| Verdict | Meaning | Who Can Issue | Effect |
|---------|---------|---------------|--------|
| SEAL | Proceed — safe, constitutional | A-VALIDATOR only | Execution authorized |
| VOID | Halt — unconstitutional or dangerous | A-AUDITOR, A-VALIDATOR | Execution blocked |
| 888_HOLD / SABAR | Pause — needs human review | Any agent | Sovereign must approve |
| PARTIAL | Proceed with conditions | ASI only | Conditions must be met |
Epistemic labels (on claims within any output):
OBS — Direct observationDER — Derived from OBSINT — InterpretationSPEC — Specification/planPer USER.md rules — verdicts only, no option lists:
✅ Done: [what happened]
⚠️ SABAR: [risk, safe default chosen, approval needed only if Arif disagrees]
🛑 VOID: [stopped, why]
No bullet lists of 3 possible approaches. No "would you prefer A or B?" Pick the best one, defend it.
Standard: Google A2A Protocol v0.3.0
AAA Gateway A2A skills:
agent-dispatch — non-blocking task dispatch (HOLD required)agent-handoff — governed delegation (HOLD required)status-query — read-only task/run status (on-demand)Transports:
/a2a/events — server-push to subscribed agentsA2A Agent Card schema:
{
"protocol_version": "0.3.0",
"id": "agent-id",
"name": "Agent Name",
"url": "https://example.com/a2a",
"preferred_transport": "sse",
"capabilities": { "streaming": true, "push_notifications": false },
"skills": [{ "id": "skill-id", "approval_policy": "hold|on-demand" }]
}
1. Design Proposal — clear, specific recommendation
2. Rationale — why this approach (with evidence cited)
3. Trade-offs — what was considered and rejected
4. Integration Points — how it fits existing system
5. F1 Reversibility Check — how to undo if wrong
6. Constitutional Compliance — F1-F13 check results
1. Implementation — the code
2. Test Coverage — tests written
3. Constitutional Check — floor validation
4. Diff Summary — what changed
5. Receipt — execution log reference for VAULT999
1. Review Summary — Pass/Fail per file
2. Constitutional Audit — F1-F13 check results
3. Issues Found — severity: CRITICAL, HIGH, MEDIUM, LOW
4. Verdict — SEAL, VOID, or 888_HOLD
5. Recommendations — specific fixes required
6. Evidence — citations for all findings
1. Validation Report — all checks passed
2. Deployment Plan — strategy (canary/blue-green)
3. Constitutional SEAL — F1-F13 compliance
4. Approval Chain — Human + Auditor + Validator signatures
5. VAULT999 Receipt — immutable deployment record
Every action generates this audit record:
{
"receipt_id": "uuid",
"timestamp": "iso8601",
"agent_id": "agent://arifos/{role}",
"session_id": "uuid",
"request": {
"intent": "string",
"tools_requested": ["tool_name"],
"files_accessed": ["path"]
},
"policy_check": {
"agent_authorized": true,
"tools_allowed": true,
"within_boundaries": true,
"constitutional_passed": true
},
"execution": {
"tools_executed": ["tool_name"],
"files_modified": ["path"],
"files_created": ["path"],
"files_deleted": ["path"]
},
"verdict": {
"status": "SEAL|VOID|888_HOLD",
"floors_triggered": ["F1", "F2"],
"human_approval": "APPROVED|PENDING|REQUIRED"
},
"vault": {
"sealed_to_vault999": true,
"merkle_hash": "sha256"
}
}
Complete decision record for every significant action:
replay_artifact:
├── prompt_input (original_prompt, constitutional_context, agent_state)
├── tool_call_chain[] (step, timestamp, reasoning, constitutional_check, result)
├── file_diffs[] (before/after hash, diff_stats, constitutional_review)
├── command_outputs[] (command, exit_code, stdout, agent_interpretation)
├── final_decision
│ ├── verdict: SEAL|VOID|888_HOLD|PARTIAL|SABAR
│ ├── constitutional_basis (per floor)
│ ├── tri_witness: {human, ai, system, W₃}
│ ├── confidence: {G_Genius, Omega_Uncertainty, overall}
│ ├── floors_violated[] (if VOID)
│ └── required_approvals[] (if HOLD)
└── reflection_metadata (trainable_insights[], review_status)
Schema source: /root/arifOS/docs/agents/forensic-replay.yaml
AGI proposes → CandidateAction + CapabilityClaim
ASI evaluates → VerdictCode + Ω_ortho + Floor compliance
APEX authorizes → ActorBinding + CapabilityToken
Vault persists → 999_SEAL
| Context | Injected | |---------|---------| | New session | SOUL.md + USER.md + MEMORY.md + daily memory | | Earth/subsurface task | GEOX context before speaking confidently | | A2A dispatch | Agent card + skill ID + approval_policy | | Cron/auto-prompt | HEARTBEAT.md + last heartbeat state | | AGI → ASI handoff | CandidateAction + CapabilityClaim + risk_tier | | ASI → APEX | VerdictCode + Ω_ortho + Floor compliance | | Forge execution | ActorBinding + CapabilityToken + arifos://forge manifest |
Agents listen for:
/root/arifOS/docs/agents/system-prompts.yaml/root/arifOS/docs/agents/agent-identity.yaml/root/arifOS/docs/agents/capability-manifest.yaml/root/arifOS/docs/agents/event-bus.yaml/root/arifOS/docs/agents/forensic-replay.yaml/root/sites/aaa/a2a/agent-card.jsondevelopment
Governed intelligence skill for AAA as the abstraction, attestation, and abduction control plane across arifOS, APEX, A-FORGE, GEOX, WEALTH, WELL, and the ariffazil profile repository. Use when the user asks to explain or design AAA, route agentic work, reduce chaos/entropy in an arifOS federation task, create AREP/task declarations, classify risk, plan multi-repo changes, review governance boundaries, or translate human intent into evidence-backed, authority-safe, recursively agentic workflows. Provides deterministic F1-F13 floor checking, bounded abduction, and FederationReceipt composition.
development
Check every skill’s “use when” and “do not use when” clauses for collisions, missing negatives, and vague verbs like “help,” “assist,” or “improve.” Load when linting, reviewing, or validating trigger boundaries.
development
Bootstrap, design, and package new skills. Load when capturing user intent for a new skill or drafting its initial instruction framework.
content-media
Diagnose which federation services are up, down, or drifting. Produce a prioritized remediation plan.