โšก Harness Runtime Control Center
Active Agents๐Ÿค–
3
Registered & Scoped
Pending Approvalsโœ‹
0
Human-in-the-loop gated
Total Executionsโšก
0
Through Harness Boundary
Evidence Manifests๐Ÿ“œ
0
SHA-256 Verified Trails
HARNESS RUNTIME EXECUTION PIPELINE
1
GOAL
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2
CONTEXT
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3
PLAN
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4
SCOPE CHECK
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5
PERMISSION
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6
RISK GATE
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7
APPROVAL
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8
EXECUTE
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9
OBSERVE
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10
VERIFY
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11
AUDIT
โ†’
12
LEARNING
Recent Executions View all โ†’
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Pending Approval Queue View all โ†’
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01 AGENT REGISTRY

No agent is unrestricted. Every agent possesses explicit identity, scope, whitelist, and risk profile.

Agent Model Status Risk Profile Allowed Actions Allowed Tools Memory Scope
Execute Controlled Agent Task
Live Execution Trace
Submit a task to observe the end-to-end Harness loop in real-time.
06 APPROVAL GATE (HUMAN-IN-THE-LOOP)

High-risk actions require explicit server-side authorization. Cannot be bypassed by frontend.

ID Agent Action Risk Level Reasons Requester Status Actions
07 & 08 EXECUTION RUNTIME TRACES

Full execution history through Scope โ†’ Permission โ†’ Risk โ†’ Execution โ†’ Observation โ†’ Verification.

Task ID Agent Goal Status Plan Steps Verified Evidence SHA-256 Timestamp
04 TOOL PERMISSION ENGINE

Tool registry and capability sandbox. No tool can be invoked without explicit agent permission.

Tool ID Name Description Required Level Side Effect Safe Credentials Boundary
03 SCOPE POLICY ENGINE

Defines what agents can and cannot do across domains, resources, actions, and targets.

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02 CONTEXT & MEMORY RUNTIME

Scoped memory store with provenance, sensitivity, and cross-agent boundary isolation.

ID Scope Key Sensitivity Provenance Timestamp
11 AUDIT & EVIDENCE RUNTIME

Cryptographically verifiable execution trail. Proves WHO, WHAT, WHY, WHEN, UNDER WHICH POLICY with WHAT EVIDENCE.

Audit ID Task ID Actor / Agent Action Policy Verdict Risk Verification Evidence SHA-256
10 RECOVERY RUNTIME

Failure capture, retry budget, state preservation, compensation, and escalation trajectories.

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12 LEARNING RUNTIME

Execution evaluation and feedback loop. Proposes rule and prompt improvements without automatic privilege escalation.

Event ID Task ID Agent Status Learning Signal Proposed Improvement Timestamp
FOUNDATION MODEL ADAPTERS

FlyTrustAgent is model-agnostic. Foundation models sit beneath the Harness Control Layer.

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