# Proof Gradient · The Agent Evolution Protocol
**One agent tries. Proof decides. The network evolves.**
GoalOS gives Direction. PlanOS gives Strategy. SkillOS gives Capability. Proof Gradient gives Evolution.
## Executive result
Status: **PASSED**
Agents: **384** · Roles: **20** · Releases: **12** · Accepted skills: **7**
Proof Gradient holdout success: **0.3523** · Static coordination: **0.1656** · Unverified propagation: **0.0453**
## Mechanism
```text
attempt
→ trace
→ skill
→ proof
→ gradient
→ upgrade
→ better attempt
```
## Proof gates
- ✅ **Holdout success uplift over static coordination** — required >= 6.0 percentage points; observed 18.67 pp
- ✅ **Value capture uplift over static coordination** — required >= 3.0 percentage points; observed 4.55 pp
- ✅ **Proof Gradient beats unverified propagation** — required >= 2.0 percentage points success uplift; observed 30.70 pp
- ✅ **Risk breach ceiling** — required <= 7.5%; observed 0.00%
- ✅ **Negative-control rejection** — required >= 95% rejected; observed 100.00%
- ✅ **Skill compounding release curve** — required final value capture > release 0 value capture; observed 0.0127 delta
## Baselines
| Mode | Success | Quality | Risk breach | Value capture |
|---|---:|---:|---:|---:|
| single | 3.83% | 40.01 | 1.87% | 21.18% |
| pool | 2.89% | 38.41 | 2.42% | 19.77% |
| static | 16.56% | 46.42 | 0.00% | 26.19% |
| unverified | 4.53% | 40.69 | 0.00% | 21.16% |
| proof_gradient | 35.23% | 51.05 | 0.00% | 30.74% |

## Skills Used
### Attempt Trace Capture
- Layer: Observation
- Purpose: Capture every agent attempt as reusable evidence instead of losing the operational lesson after completion.
- Input: task, agent, role quorum, outcome, risk event, value outcome
- Output: structured trace with provenance and measurable result
- Verifier: trace schema, deterministic seed, holdout isolation check
### Skill Distillation
- Layer: Capability Extraction
- Purpose: Compress successful repeated work patterns into candidate reusable skills.
- Input: high-quality traces and task requirement vectors
- Output: candidate skill with domain, vector, cost, and risk profile
- Verifier: candidate must improve validation tasks before propagation
### Proof-Gated Selection
- Layer: Evolution
- Purpose: Accept only skills that survive validation, holdout, transfer, and risk gates.
- Input: candidate skill and isolated validation cases
- Output: accepted, rejected, revised, or retired skill decision
- Verifier: uplift threshold, transfer threshold, risk breach ceiling
### Gradient Scoring
- Layer: Selection Signal
- Purpose: Convert proof outcomes into a gradient that decides what the network should learn next.
- Input: uplift, confidence, transfer score, risk penalty, reuse potential
- Output: signed evolution gradient for each candidate skill
- Verifier: positive gradients must outperform static coordination on holdout
### Network Propagation
- Layer: Routing Upgrade
- Purpose: Share verified skills across the agent network while preventing unverified capability drift.
- Input: accepted skill, role map, skill compatibility, release gate
- Output: network-wide routing upgrade
- Verifier: post-propagation holdout score and negative-control rejection
### Capability Governance Twin
- Layer: Governed Release
- Purpose: Simulate the release of a new capability before allowing it to influence network routing.
- Input: skill candidate, release route, policy boundary, rollback path
- Output: governed release decision with public receipt
- Verifier: policy gate, rollback gate, verifier coverage gate
### Adversarial Negative Control
- Layer: Robustness
- Purpose: Inject plausible but harmful skills to verify that proof, not popularity, decides propagation.
- Input: poisoned skills, overfit skills, high-risk shortcuts
- Output: rejection receipt and risk-breach evidence
- Verifier: bad skills must receive negative or sub-threshold gradients
### Executive Receipt Rendering
- Layer: Communication
- Purpose: Turn the proof into a public, non-technical, inspectable artifact.
- Input: metrics, gates, baselines, skills, evidence hashes
- Output: JSON receipt, Markdown report, badge, webpage
- Verifier: artifact existence, public boundary, link integrity
## Public boundary
This proof is a deterministic benchmark and public mechanism demonstration. It does not claim achieved superintelligence, audited customer ROI, investment returns, financial advice, legal advice, medical advice, employment advice, credit advice, token advice, or Kardashev Type II civilization. It shows a testable mechanism: proof-gated skill propagation can outperform static or unverified coordination under the stated benchmark assumptions.
