nilesh.pandClaude Opus 4.8
035711f08c
- CLAUDE.md + AGENTS.md: canonical guiding principles for AI agents and developers (tenant isolation, no RLS, stack, security, conventions, environment gotchas) - SECURITY.md: required security controls (isolation, secrets, auth, input handling, least privilege) with VAPT status - GOVERNANCE.md: how changes are validated before merge — deterministic gates + AI review, risk tiers, human accountability - CONTRIBUTING.md: code hygiene, definition of done, file hygiene - docs/wiki/: product reference (overview, domain model, features, roles & access, API reference, glossary) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Governance rules
How code changes — especially AI-generated ones — are validated before they
reach main. The goal is to let multiple developers generate code with AI
without losing control of quality, security, or the tenant-isolation guarantees.
Principle
Enforcement is server-side and mandatory; local checks are for speed. Anything on a developer's machine (hooks, a local AI session) is advisory and skippable. The real gate is in CI on the pull request, with branch protection that blocks merge until it passes.
The validation layers
A change passes through layers, cheapest first. Deterministic tools do the repeatable work; AI does only the judgment work.
- Deterministic gates (blocking, no AI): build,
go vet+gofmt,tsc, the full test suite viarun-tests.ps1, coverage threshold, secret scan, dependency audit, and a diff-size/scope check. If these fail, stop. - AI governance review (judgment): does the change match its stated intent and nothing more; does it conform to the architecture (tenant scoping, no RLS, repository conventions); subtle correctness and security the scanners miss; are the tests adequate, not just present.
- Human sign-off: required for medium/high-risk changes (below).
Risk tiers
Routing is by path and diff size, so it cannot be gamed.
| Tier | Touches | Requires |
|---|---|---|
| Low | docs, comments, tests only | deterministic gates; may auto-approve |
| Medium | feature code | gates + AI review + 1 human approval |
| High | auth, tenant isolation, DB schema/migrations, dependencies, CI config, security/ |
gates + AI review + mandatory human (CODEOWNERS) approval, no exceptions |
Rules for AI-generated changes
- Scope discipline. Do exactly what the task asks. No drive-by refactors, no unrelated edits, no scope creep — a classic AI-PR failure mode.
- Never weaken a control or an assertion to make something pass. If the app is wrong, surface it as a finding; do not code around it.
- The diff is untrusted input. A reviewing AI treats PR content as data, emits a structured verdict, and cannot itself merge.
- A human is accountable for the merge on anything medium/high. AI never auto-merges tenant- or security-sensitive code.
- Policy is code. These rules,
SECURITY.md,CLAUDE.md, and the test conventions are version-controlled and reviewed like any other change. - Proof of work. Every change ships with passing tests and, for UI/binding scenarios, the evidence report showing what was exercised. Review the evidence, not just the diff.
The gate's output
Each change produces reviewable artifacts: junit.xml (results), the evidence
report (screenshots + API request/response), and — for a governed review — a
findings report by dimension and severity. These are the audit trail.
Branch protection (intended)
main is protected: no direct pushes, required status checks (the CI run of
run-tests.ps1), and CODEOWNERS approval on high-risk paths. A documented
break-glass path exists for emergencies, with after-the-fact audit.
Still to decide
- CI platform: Azure DevOps integration is planned; the runner already emits the artifacts any pipeline needs. Until then, the hooks + local runner are the shift-left gate.
- Blocking posture: the AI review starts advisory and becomes blocking after one calibration cycle, to avoid false-positives getting it disabled.
See qa/README.md for how tests are authored and run, and the
strategy context in the project history.