feat(ci): v0.9.0 — Distribution & Expansion milestone complete
---ci---
project: ci
phase: 6
milestone: v0.9
status: complete
artifacts:
tags: [v0.9.0]
decisions:
- id: D-047
decision: v0.9 theme = Distribution & Expansion
rationale: npm publish + OpenAI/Anthropic backends + agent flesh + parallel execution
confidence: 0.92
- id: D-049
decision: Feature milestone — patch tags v0.8.1-v0.8.6 then v0.9.0
rationale: OpenAI backend, agent flesh, npm publish all feat
confidence: 0.95
- id: D-059
decision: Rename OllamaBaseBackend to LLMBaseBackend + thin OllamaBaseBackend subclass
rationale: 15 of 17 methods backend-agnostic
confidence: 0.92
- id: D-060
decision: OpenAI/Anthropic backends use native fetch() not SDK packages
rationale: No dependency bloat; fetch native in Node 18+
confidence: 0.85
- id: D-066
decision: Concurrency limiter internal (no p-limit dependency)
rationale: 15 lines; avoids dependency for trivial feature
confidence: 0.90
- id: D-067
decision: Promise.allSettled for review agents at orchestrator lines 373-400
rationale: Current sequential loop replaced with parallel execution
confidence: 0.88
requirements:
covered: [PUBLISH-01, PUBLISH-02, PUBLISH-03, PUBLISH-04, OPENAI-01, OPENAI-02, OPENAI-03, OPENAI-04, OPENAI-05, FLESH-01, FLESH-02, FLESH-03, FLESH-04, FLESH-05, ANTHROPIC-01, ANTHROPIC-02, FLESH-06, FLESH-07, NPM-01, NPM-02, PARALLEL-01, PARALLEL-02, PARALLEL-03, INTEG-01, INTEG-02, INTEG-03, INTEG-04, INTEG-05]
---/ci---
6 phases, 28 tasks, 4077 net lines added, 57 test suites, 527 tests, zero stub agents
This commit is contained in:
Jon Chery
@@ -8,6 +8,20 @@ CIAgent (Continuous Intelligence) is an autonomous-first software engineering ha
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**The git log IS the project memory.** Every decision, escalation, lesson learned, and verification result is encoded in commit messages using structured `---ci---` YAML blocks. An agent's first impulse to gather context is `git log`, not file reads. Another agent with access to only commit messages (no code, no diffs) can reconstruct the project state completely.
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## Intelligence Backends
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CIAgent supports 5 intelligence backends. Set the appropriate environment variable and use `--backend` to select:
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| Backend | Setup | Usage |
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|---------|-------|-------|
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| **OpenAI** | `export OPENAI_API_KEY=sk-...` | `ciagent run --backend openai` |
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| **Anthropic** | `export ANTHROPIC_API_KEY=sk-ant-...` | `ciagent run --backend anthropic` |
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| **Ollama Local** | `ollama serve` (localhost:11434) | `ciagent run --backend ollama-local` |
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| **Ollama Cloud** | `export OLLAMA_CLOUD_API_KEY=...` | `ciagent run --backend ollama-cloud` |
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| **Opencode** | `npm i -g opencode` | `ciagent run --backend opencode` |
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Auto-detection (`--backend auto`, the default) tries: opencode → openai → ollama-local → ollama-cloud → anthropic.
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## Installation
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From source (package not yet published to npm):
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@@ -38,6 +52,11 @@ ciagent run plan
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ciagent run execute
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ciagent run verify
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# Run with specific backends
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ciagent run --all --backend openai
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ciagent run --all --backend anthropic
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ciagent run --all --backend ollama-local
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# Execute an ad-hoc task
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ciagent quick "Add authentication middleware"
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@@ -58,7 +77,7 @@ ciagent rollback 1
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ciagent ship 1
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```
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## Git-Native Architecture (v0.2.0)
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## Git-Native Architecture (v0.9.0)
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### The Commit Schema
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@@ -246,16 +265,25 @@ Decisions are committed to git as `decision` type commits. The audit trail is `g
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| researcher | Domain research | Logs assumptions, never flags for human |
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| tester | Integration/e2e tests | Detects and runs existing test files, never writes tests |
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| challenger | Plan stress-testing | Binding verdicts, only escalates <0.60 |
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| security-auditor | Security audit | Auto-dispositions threats |
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| security-auditor | Security audit | Auto-dispositions threats (STRIDE + CWE) |
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| debugger | Bug fixing | Auto-fixes when confidence > threshold |
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| Others | Various | Delegates to active intelligence backend |
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| code-reviewer | Code review | 3-persona review (security, performance, maintainability) |
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| doc-writer | Documentation | Auto-updates ROADMAP/REQUIREMENTS/PROJECT.md |
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| doc-verifier | Doc audit | Cross-checks docs vs. codebase (agent count, version, test count) |
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| ideation-agent | Improvement ideas | Feeds uncovered requirements and repeated lessons into planning |
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| roadmapper | Roadmap creation | Groups requirements by phase, generates success criteria |
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| plan-checker | Plan validation | Checks structure, IDs, must-haves, wave order, requirement coverage |
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| project-researcher | Ecosystem research | Detects frameworks, APIs, patterns, tooling from package.json |
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| research-synthesizer | Research merge | Cross-references findings across .ciagent/ documents |
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| solution-writer | Solution docs | Produces structured solution documents from plan + requirements |
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| phase-researcher | Phase research | Extracts decisions, lessons, risks from git log for a specific phase |
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### Verification Layers
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1. **Structural**: File existence, import/export wiring, no stubs
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2. **Behavioral**: Test infrastructure and requirement traceability (partially implemented — static analysis, no test generation yet)
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3. **Security**: Regex-based threat pattern scanning with auto-disposition (partially implemented — no STRIDE analysis yet)
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4. **Code Quality**: Regex-based code quality checks (partially implemented — no multi-persona review yet)
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2. **Behavioral**: Test execution and requirement traceability — runs test framework, parses results, reports pass/fail per suite
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3. **Security**: STRIDE threat pattern scanning with CWE mapping and confidence-based auto-disposition
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4. **Code Quality**: 3-persona code review (security, performance, maintainability) with P0/P1/P2 findings
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## Specification Format
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@@ -293,9 +321,8 @@ Each escalation is committed as an `escalation` type commit. Resolved escalation
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## Current Limitations
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- **Agent implementations**: 5 core agents have intrinsic logic (planner, executor, verifier, researcher, tester); 13 agents delegate to backends. Full LLM-powered agent behavior requires an intelligence backend.
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- **Agent implementations**: All 18 non-orchestrator agents have intrinsic mechanical logic. Full LLM-powered agent behavior requires an intelligence backend (OpenAI, Anthropic, Ollama, or Opencode).
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- **Package not published to npm**: Install from source only until a publishing pipeline is configured.
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- **Behavioral/Security/Quality verification layers**: Partially implemented — structural verification is complete; behavioral does static analysis; security does regex-based threat scanning; quality does regex-based code quality checks.
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## Differences from Learnship
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