Alpha-stage prototype · Phase 6 checkpoint · v0.1.0 · MIT License

Evidence-First
Harness

Deterministic assurance for AI-generated code. Treats every AI patch as an untrusted proposal — routes outputs through deterministic policy gates that produce evidence bundles.

"No agent-generated change may be accepted unless every material claim introduced by the change is linked to sufficient, reproducible, risk-adjusted evidence."

Repository metrics reflect the current public repository state at the time of publication and may change.

Smoke Test

[ Quick Start ]

01 Clone the repository
git clone https://github.com/rmax-ai/evidence-first-harness.git
02 Install dependencies
cd evidence-first-harness && uv sync --extra dev
03 Run 73 tests in ~4 seconds
uv run pytest tests/ -q
04 Full E2E smoke test (~90s)
uv run efh run --repo .

[ Representative Run ]

sharn@evidence-harness:~ ~90s
$ efh run --repo .

workflow_started    run_id=run_3da28c6662d9
worktree_created    base_commit=9007ebb1

specification_agent_call   opus-4-6   in=294   out=4096
planner_agent_call         sonnet-5   in=430   out=770
implementation_agent_call  deepseek   in=276   out=34

evidence_executed  formatting  ruff     fail
evidence_executed  lint        ruff     fail
evidence_executed  type_check  pyright  fail
evidence_executed  secret_scan secrets  pass
evidence_executed  tests       pytest   fail

decision_rendered  decision=repair_required
  mandatory_failed=4  passed=1  tier=3

│ Agent              Model                  In    Out │
├──────────────────┼──────────────────┼──────┼──────┤
│ specification      claude-opus-4-6       294   4096 │
│ planner            claude-sonnet-5       430    770 │
│ implementation     deepseek-chat         276     34 │
├──────────────────┼──────────────────┼──────┼──────┤
│ TOTAL                                   1000   4900 │

The transcript below is a representative smoke-test run from the alpha harness. It shows the intended separation of roles: LLM agents produce implementation and review artifacts, while deterministic checks and policy decide the workflow outcome. Exact runtime, token counts, and cost vary with provider pricing, API behavior, cache state, model routing, and repository state. Treat the displayed cost as a run-specific estimate, not a guaranteed current API price.

Estimated run cost: approximately $0.1125 under current pricing assumptions as of 2026-07-13, using Sonnet 5 introductory pricing ($2/$10 per 1M tokens). Under standard Sonnet 5 pricing ($3/$15 from 2026-09-01), the estimate is $0.1170. These estimates exclude hidden/tool overhead and provider-side accounting differences. The cost in the transcript reflects the project's original pinned pricing assumptions.

Architecture

Illustrative architecture — not a benchmark or production deployment. In the shown configuration, LLM agents produce implementation and review artifacts; deterministic checks and policy decide the workflow outcome.

pipeline.svg 17 nodes
Evidence-First Harness Pipeline — 17-node workflow
#ComponentTypeControls
[01]Specification agentLLM AGENTInterprets tasks, derives requirements
[02]Planner agentLLM AGENTProposes implementation plan
[03]Implementation agentLLM AGENTGenerates code in sandbox
[04]Independent test agentLLM AGENTGenerates additional tests (stubbed in alpha)
[05]Adversarial review agentLLM AGENTIdentifies unsupported claims (stubbed in alpha)
[06]Explanation agentLLM AGENTConverts evidence to report (stubbed in alpha)
[07]Policy engineDETERMINISTICRequired evidence, thresholds, approval roles
[08]Decision engineDETERMINISTICAccept / reject / repair decision
[09]Sandbox managerDETERMINISTICIsolation, permissions, timeouts
[10]Evidence executorsDETERMINISTICRun checks, record EvidenceRecords
[11]AST analyzerDETERMINISTICImpact analysis, test selection
[12]Provenance recorderDETERMINISTICHash-chained event stream

Model Routing & Pricing

[ Agent Routing ]

AgentModelProviderLiveInOut
Specificationclaude-opus-4-6Anthropic2944096
Plannerclaude-sonnet-5Anthropic430770
Implementationdeepseek-chat‡DeepSeek27634
Independent Testclaude-haiku-4-5Anthropic00
Adversarial Reviewgemini-3.5-flashGoogle00
Explanationgemini-3.5-flashGoogle00

‡ deepseek-chat is a compatibility alias for deepseek-v4-flash. Alias deprecated 2026-07-24.

[ Pricing — USD per 1M tokens, as of 2026-07-13 ]

ModelInput $Output $
claude-opus-4-6$5.00$25.00
claude-sonnet-5$2.00$10.00
Introductory pricing through 2026-08-31. $3/$15 from 2026-09-01.
claude-haiku-4-5$1.00$5.00
deepseek-v4-flash$0.14$0.28
Cache-miss input; cache-hit is $0.0028. Alias: deepseek-chat until 2026-07-24.
gemini-3.5-flash$1.50$9.00
Standard tier visible pricing. Actual cost may differ by tier/region.

The harness routes implementation and evaluation through distinct roles. In this alpha, 3 of 6 agent roles are live LLM agents and the remaining evaluator roles are stubbed or deterministic placeholders.

Evidence Tiers

Tier 3 Automated

formatting, lint, type check, targeted tests, secret scan

Tier 2 Code owner

+ integration tests, security scan, mutation testing

Tier 1 Code owner + security owner

+ contract tests, dependency scan, performance, rollback