aicf-core

# AICF-Core Development Checklist & Roadmap ## 1. Baseline Features for an "AICF‑Core" Repo ----------------------------------------------------------------------- Component Purpose Key considerations ----------------------- ----------------------- ----------------------- **AICF spec document** The authoritative Must be (`AICF_SPEC.md`, format spec, fields, human‑readable + versioned) encodings, versioning machine‑verifiable; rules clearly document backward/forward compatibility, version tags, optional vs required fields. **Writer / Serializer** Given a memory Support multiple representation, produce encoding options a valid AICF file / (e.g. JSON, compressed byte stream / binary, fallback plain). **Reader / Parser / Read AICF files, Validate version, Deserializer** validate integrity, detect corruption, produce memory handle optional fields, structures errors gracefully. **Tests / Fuzzing / Ensure writer + reader Unit tests, property Validation** roundtrip correctness, tests, negative tests edge cases, corrupt (malformed input), files cross-version compatibility tests. **Benchmarks / Measure time, memory, Use fixed data sets; Performance suite** compression ratio, etc. produce reproducible metrics; publish artifacts. **Examples / Show real-world usage Minimal working code in Integrations** (e.g. integrate with Python, JS, or more context engine, openai, languages. embedding store) **Adapters / Bindings If core is in one Ensure boundary safety, (optional)** language, expose version sync. bindings (e.g. a Python wrapper of a Rust core) **CLI or helper tools** Validate / inspect / Useful for debugging diff AICF files, and migration. migration tools **Versioning & Ability to migrate from Provide automatic Migration utilities** AICF v1 → v2, detect migration logic or older versions tools. **Documentation & README, CHANGELOG, Must be clear so reference** usage patterns, external users can tradeoffs, error codes adopt safely. **Security / privacy Guidelines for Document how to avoid considerations** embedding sensitive leaking PII / secrets. content, encryption, redaction **License / Clear licensing, CLA if Encourages community. contribution needed, contributor guidelines** code of conduct ----------------------------------------------------------------------- ------------------------------------------------------------------------ ## 2. Risks & Pitfalls - **Spec drift** --- implementation diverges from the spec doc over time.\ - **Backward/forward compatibility breakage** --- changes in field definitions, compression logic, or required fields can break existing stored contexts.\ - **Silent data loss** --- if summarization, filtering, or truncation logic is too aggressive, important context might be lost.\ - **Performance regressions** --- as features are added, performance might degrade (esp. on large histories).\ - **Interoperability problems** --- users in different languages or platforms might interpret formats differently.\ - **Corruption handling** --- AICF files might be truncated, partially overwritten, or corrupted in transit; parser should fail safely.\ - **Security leakage** --- users might accidentally embed secrets in AICF; or read memory from other sessions.\ - **Version sprawl** --- many minor versions without clear migration path.\ - **Complexity creep** --- core becoming too big, mixing optimization, logic, UI, etc. ------------------------------------------------------------------------ ## 3. Draft v1 Readiness Checklist ### Spec - [ ] `AICF_SPEC.md` outlining all fields, types, optional vs required\ - [ ] Versioning plan (e.g. `v1.0.0` with semantic versioning)\ - [ ] Examples of minimal & full AICF files (in JSON / binary) ### Core Implementation - [ ] Writer / serializer that produces valid output matching spec\ - [ ] Reader / parser that can validate & recover structures\ - [ ] Round-trip tests (write → read → compare) ### Testing - [ ] Unit tests for edge cases (empty, large, missing optional fields)\ - [ ] Negative tests (malformed data, truncated streams)\ - [ ] Cross-version compatibility tests (if multiple spec versions)\ - [ ] Performance tests & benchmarks ### Migration & Version Tools - [ ] Logic to identify version of AICF file\ - [ ] Migration functions for future versions\ - [ ] CLI "upgrade" / "downgrade" commands ### Tooling / CLI - [ ] `aicf-inspect` (view structure, metadata)\ - [ ] `aicf-diff` (compare two AICF files, changes)\ - [ ] `aicf-validate` (check compliance) ### Documentation & Examples - [ ] README with usage guide\ - [ ] Code examples (ideally in multiple languages or languages your users will use)\ - [ ] FAQ / "gotchas" (e.g. embedding limits, missing fields) ### Security / Privacy - [ ] Guidelines on how to manage PII / secrets in stored contexts\ - [ ] Optionally, encryption or secure wrapping (if needed)\ - [ ] Safe defaults (e.g. default exclude secrets, redact sensitive keys) ### Release Infrastructure / CI - [ ] Automated tests on PRs\ - [ ] Lint / static analysis\ - [ ] Benchmark runs\ - [ ] Tagging & release pipelines (npm / PyPI / etc) ### Governance & Community - [ ] LICENSE file\ - [ ] CONTRIBUTING.md & Code of Conduct\ - [ ] Issue templates / PR templates ### Stability & Deprecation Plan - [ ] Backwards-compatibility guarantees\ - [ ] Deprecation warnings & migration path for breaking changes ------------------------------------------------------------------------ ## 4. Suggestions for Collaboration / Adoption - **Language bindings early**: JS + Python at minimum; maybe Rust or Go for performance layers.\ - **Community workshop / tutorial**: show how to adopt AICF in an existing AI chat stack.\ - **Validation library**: a small "schema validator" to help other implementers.\ - **Version compatibility matrix**: e.g. "clients v1.0 ↔ core v1.0 support reading v0.x files (with warnings)."\ - **Benchmark publish**: as releases go out, publish performance metrics to build trust.\ - **Reference implementation**: make sure your core is not too opinionated but is solid enough to serve as a baseline.\ - **Partner / adopter case studies**: show how others used AICF-Core --- to build legitimacy.