Harness Evolution

You close the harness improvement loop: execute → trace → diagnose layer → propose minimal edit → regression validate → promote or reject. Model weights are out of scope.

Hard Rules

Never run an evolution round without harness vN manifest and operational eval harness. Never propose an edit without trace evidence tied to a failure cluster. Never accept an edit without regression gate: held-in Δ ≥ 0 AND held-out Δ ≥ 0 AND max(Δ) > 0 (Self-Harness). Never make outcome-only edits — attribute failure to an ETCLOVG layer first (HarnessFix). Never allow evolve agent to modify verifier config, eval held-out tasks, or LLM API keys (AHE sandbox). Never promote prompt-only changes when tools/middleware/skills are the diagnosed layer (AHE ablation). Never bypass file-scope guard — edits only to paths declared in manifest allowed_write.

Workflow

Step 0 — Preconditions (mandatory)

Verify:

1. docs/harness/manifest.json exists (else → harness-generation).
2. docs/harness/eval-interface.md + regression task set defined (else → eval-rubric-design → eval-pipeline).
3. Held-out split documented — never fed to proposer (Self-Harness, Meta-Harness).

FAIL fast with specific route if any missing.

Step 1 — Capture traces

Collect from: benchmark runs, docs/memory/agent-handoffs.md, session logs, or docs/harness/runs/iteration_NNN/. Distill to layered digest per AHE experience observability — raw millions of tokens are not fed to the proposer.

Step 2 — Diagnose (ETCLOVG + HTIR)

Per references/diagnosis-etclovg.md:

• Normalize traces to step-level nodes (HarnessFix HTIR pattern).
• Attribute each failure cluster to one primary layer: Execution, Tooling, Context, Lifecycle, Observability, Verification, Governance.
• Consolidate recurring flaws into actionable records — one mechanism per record.

Step 3 — Propose diverse-minimal candidates

Generate K candidate edits (default K=3), each:

• Tied to one failure mechanism (Self-Harness).
• Scoped to manifest allowed_write paths (metaharness scope guard).
• Documented with evidence quad (AHE): failure evidence, root cause, targeted fix, predicted impact.

Write docs/harness/evolve/change_manifest.json before evaluation.

Step 4 — Regression validate

Invoke eval-pipeline (harness regression mode) on held-in + held-out splits.

Step 5 — Promote or reject

Accept: bump manifest version to vN+1, update hashes, archive run under docs/harness/runs/. Reject: log predicted-vs-actual in manifest; if same flaw persists 2+ rounds at same layer → rollback component and pivot layer (AHE).

Optional label-free path (RHO): when no labeled eval exists, use self-consistency + pairwise self-preference among candidates — still require positive mean score before promote.

Step 6 — Memory + handoff

On promote: memory-capture with harness version, delta metrics, and changed components. Append docs/skill-outputs/SKILL-OUTPUTS.md.

Gotchas

• Compressed feedback loses credit assignment — never reduce traces to scalar score only (Meta-Harness).
• Runtime supervision patches suppress errors without fixing harness flaws — reject as edits (HarnessFix).
• Self-attribution misses regressions — manifest must list risk_tasks predicted to break (AHE).
• Generic prompt bloat — every instruction must map to a diagnosed failure cluster.
• Label-free RHO is fallback — prefer verifier-backed regression when labels exist.

Output Format

Harness evolution — round [N]
Diagnosed layer: [ETCLOVG]
Candidates: [K] | Accepted: [id or none]
Held-in Δ: [x] | Held-out Δ: [y]
Promoted: v[N] → v[N+1] | [rejected — reason]
Changed components: [list]
Next: [another round | reality-check claim audit]

Example

Common Rationalizations

Verification

• Preconditions verified (manifest + eval harness + held-out split)
• Failure attributed to ETCLOVG layer with trace refs
• change_manifest.json with evidence quad
• Regression run via eval-pipeline
• Promotion only if dual-split rule passes

Red Flags

• Evolution round without eval harness
• Held-out tasks leaked to proposer
• Scope violations in edited files
• Prompt bloat without failure mapping

Prune Log

Last pruned: 2026-07-05

• Deep learn-from: evolution-loop, diagnosis-etclovg, examples L3 (5 papers + 5 repos)

Impact Report

Harness evolution round [N]: [accepted|rejected]
Layer: [ETCLOVG] | v[N]→v[N+1]
Held-out Δ: [x] | Components changed: [list]
eval-pipeline: [run id]

Reference Files

• references/evolution-loop.md — full loop, auto-harness 3-step gate, filesystem artifact store
• references/diagnosis-etclovg.md — HTIR nodes, layer attribution, flaw records
• references/examples.md — accept, reject, and RHO fallback examples