Finish guardrails MVP floor

[terisuke]

Summary

• add scripted scenario and replay harness coverage for guardrail workflows
• harden the guardrail plugin with MVP floor state tracking and prompt injection
• align provider admission with current Z.AI coding-plan, OpenAI OAuth/Codex, and OpenRouter evaluation lanes
• keep the thin distribution launcher working under ESM and repo-local .env usage

Verification

• cd packages/opencode && bun test test/scenario/guardrails.test.ts
• cd packages/opencode && bun typecheck
• git push hook: bun turbo typecheck
• live smoke: openai/gpt-5.4 -> OPENAI_OK
• live smoke: zai-coding-plan/glm-5.1 -> ZAI_PLAN_OK

Closes#7
Closes#13

[Copilot]

Pull request overview

This PR completes the “guardrails MVP floor” by adding deterministic scenario replays for guardrail workflows, hardening the guardrail plugin with file-backed runtime state + enforcement gates, and aligning provider admission with the updated Z.AI coding-plan lane and OpenAI OAuth/Codex/OpenRouter evaluation usage—while keeping the distribution launchers working under ESM and supporting repo-local .env loading.

Changes:

• Add a scripted replay catalog + runtime harness to exercise guarded commands end-to-end using a deterministic fake LLM server.
• Harden the guardrail plugin with MVP-floor state tracking (reads/edits/factcheck/review freshness), version baseline checks, and context-budget enforcement injected into review/ship/handoff prompts.
• Update provider admission to include zai-coding-plan, broaden allowlists, and bump the OpenRouter evaluation agent default model.

Reviewed changes

Copilot reviewed 12 out of 14 changed files in this pull request and generated 1 comment.

Show a summary per file

File	Description
packages/opencode/test/scenario/replay.ts	Adds scripted replay definitions (expected prompts/results/tool steps) for guarded workflows.
packages/opencode/test/scenario/harness.ts	Adds an Effect-based replay runner that boots real session/plugin layers with a fake LLM server and asserts artifacts.
packages/opencode/test/scenario/guardrails.test.ts	Expands scenario coverage (provider lanes, OAuth Codex visibility, MVP-floor plugin enforcement, and replay-based executability checks).
packages/opencode/bin/opencode	Converts launcher to ESM and adds a Bun-based fallback execution path.
packages/guardrails/README.md	Updates documentation to reflect zai-coding-plan as a first-class provider lane.
packages/guardrails/profile/plugins/guardrail.ts	Implements MVP-floor plugin hardening: state tracking, baseline/version checks, context budget, and prompt injection for review/ship/handoff/compaction.
packages/guardrails/profile/opencode.json	Adds zai-coding-plan provider + expands provider/model allowlists (incl. OpenAI Codex/OAuth and OpenRouter eval set).
packages/guardrails/profile/agents/provider-eval.md	Updates provider-eval agent default model to openrouter/openai/gpt-5.4-mini.
packages/guardrails/managed/opencode.json	Mirrors profile provider enablement + allowlists for managed deployments.
packages/guardrails/bin/opencode-guardrails	Converts to ESM and adds repo-local .env discovery/loading before launching opencode with the guardrail profile.
docs/ai-guardrails/README.md	Adds references and pointers to scenario replays + ADR boundary guidance.
docs/ai-guardrails/adr/006-plugin-hardening-floor.md	New ADR defining the MVP hardening floor and explicit deferrals.
docs/ai-guardrails/adr/005-scripted-scenario-replays.md	New ADR defining the replay approach and why it’s used.
docs/ai-guardrails/adr/002-provider-admission-lanes.md	Updates admission-lane ADR to include zai-coding-plan in the standard confidential-code lane.

---

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

[Copilot]

Auth.set("openai", ...) persists credentials to the shared test auth store (Global.Path.data/auth.json). Since the test run shares OPENCODE_TEST_HOME across files, leaving this OAuth entry behind can change provider-loading behavior in unrelated tests. Add cleanup for the OpenAI auth entry (e.g., Auth.remove("openai")) in a finally block in this test or in the file-level afterEach.

Suggested change

	constproviders=awaitProvider.list()
	constopenai=providers[ProviderID.openai]
	constmodels=Object.keys(openai.models).sort()
	expect(openai).toBeDefined()
	expect(models).toEqual(
	expect.arrayContaining([
	"gpt-5.1-codex",
	"gpt-5.1-codex-max",
	"gpt-5.1-codex-mini",
	"gpt-5.2",
	"gpt-5.2-codex",
	"gpt-5.3-codex",
	"gpt-5.4",
	]),
	)
	expect(openai.models["gpt-5.4"]?.cost.input).toBe(0)
	awaitexpect(
	Plugin.trigger(
	"chat.params",
	{
	sessionID: "session_test",
	agent: "implement",
	model: openai.models["gpt-5.4"],
	},
	{temperature: undefined,topP: undefined,topK: undefined,options: {}},
	),
	).resolves.toEqual({temperature: undefined,topP: undefined,topK: undefined,options: {}})
	try{
	constproviders=awaitProvider.list()
	constopenai=providers[ProviderID.openai]
	constmodels=Object.keys(openai.models).sort()
	expect(openai).toBeDefined()
	expect(models).toEqual(
	expect.arrayContaining([
	"gpt-5.1-codex",
	"gpt-5.1-codex-max",
	"gpt-5.1-codex-mini",
	"gpt-5.2",
	"gpt-5.2-codex",
	"gpt-5.3-codex",
	"gpt-5.4",
	]),
	)
	expect(openai.models["gpt-5.4"]?.cost.input).toBe(0)
	awaitexpect(
	Plugin.trigger(
	"chat.params",
	{
	sessionID: "session_test",
	agent: "implement",
	model: openai.models["gpt-5.4"],
	},
	{temperature: undefined,topP: undefined,topK: undefined,options: {}},
	),
	).resolves.toEqual({temperature: undefined,topP: undefined,topK: undefined,options: {}})
	}finally{
	awaitAuth.remove("openai")
	}