122 lines
4.1 KiB
Markdown
122 lines
4.1 KiB
Markdown
# Workflow
|
|
|
|
## 1. Model Extraction Workflow
|
|
|
|
For detailed model extraction gates, see `docs/MODEL_EXTRACTION_WORKFLOW.md`.
|
|
|
|
The project follows this flow:
|
|
|
|
```text
|
|
Original article / representative text
|
|
-> source article record
|
|
-> source evidence excerpts
|
|
-> human-readable model card
|
|
-> machine-readable model JSON
|
|
-> regression cases
|
|
-> selector examples
|
|
-> validation report
|
|
```
|
|
|
|
## 2. Development Workflow
|
|
|
|
For each task:
|
|
|
|
1. Read `README.md` and `AGENTS.md`.
|
|
2. Check `docs/PROJECT_BRIEF.md`.
|
|
3. Modify the smallest necessary set of files.
|
|
4. Keep JSON and Markdown versions consistent.
|
|
5. Run or update validation.
|
|
6. Update reports or handoff notes.
|
|
7. Do not expand scope without confirmation.
|
|
|
|
## 3. Model Addition Workflow
|
|
|
|
When adding a new model:
|
|
|
|
1. Create a model JSON file in `models/`.
|
|
2. Create a human-readable card in `cards/`.
|
|
3. Add source article records.
|
|
4. Add source evidence excerpts.
|
|
5. Add regression cases.
|
|
6. Add selector examples if relevant.
|
|
7. Run `python scripts\rebuild_indexes.py --write`.
|
|
8. Run validation.
|
|
9. Update documentation.
|
|
|
|
## 4. Stabilization Workflow
|
|
|
|
If a model is unstable:
|
|
|
|
1. Mark `needs_stabilization: true`.
|
|
2. Add risks in `stability_profile.main_risks`.
|
|
3. Add boundary and misuse regression cases.
|
|
4. Do not upgrade to stability level A until tests pass.
|
|
|
|
## 5. Handoff Workflow
|
|
|
|
For ChatGPT-specific handoff rules, see `docs/CHATGPT_HANDOFF_RULES.md`.
|
|
|
|
At the end of each work session:
|
|
|
|
1. Summarize what changed.
|
|
2. List created and modified files.
|
|
3. Record validation status.
|
|
4. Separate assumptions from verified facts.
|
|
5. List questions that require product or CCRA judgment.
|
|
6. Suggest the smallest useful next tasks.
|
|
|
|
If the owner is going from Codex to ChatGPT, create a `reports/ChatGPT交接文档_<topic>_<YYYY-MM-DD>.md` file before ending the work session.
|
|
|
|
Before handoff, run:
|
|
|
|
```powershell
|
|
python scripts\rebuild_indexes.py --check
|
|
python scripts\validate_model_library.py
|
|
```
|
|
|
|
## 6. Supplier Request Workflow
|
|
|
|
When this repository needs a capability owned by a neighboring repository:
|
|
|
|
1. Classify the need.
|
|
2. Use `requirements/ccpe/` for expert-agent, runtime, model-governance, invocation, evaluation, or integration-registration needs.
|
|
3. Use `requirements/skills-vault/` for deterministic automation, reusable scripts, validation helpers, extraction helpers, or installable Skill needs.
|
|
4. Write one request file per missing capability.
|
|
5. Pause the dependent model extraction or implementation step unless the project owner explicitly says to solve the need locally.
|
|
6. Resume after the supplier artifact, installed Skill, or owner decision is available.
|
|
|
|
## 7. Duplex Model Extraction Workflow
|
|
|
|
Model extraction has two concurrent tracks:
|
|
|
|
```text
|
|
Workflow/tooling track -> request or build the process and supporting capabilities.
|
|
Content-processing track -> use available capabilities to extract, validate, and stabilize models.
|
|
```
|
|
|
|
Do not let the content-processing track silently absorb missing tooling work.
|
|
|
|
If a tool gap appears, record it as a supplier request and stop the blocked extraction step.
|
|
|
|
## 8. Framework Adoption Workflow
|
|
|
|
Third-party agentic frameworks such as CrewAI or LangGraph may be introduced only for concrete product implementation.
|
|
|
|
Before adoption:
|
|
|
|
1. Record the product reason.
|
|
2. Identify whether CCPE needs to supply an Agent Spec, Runtime Spec, authority rule, evaluation rule, or integration registration.
|
|
3. Identify whether skills-vault needs to supply reusable deterministic helpers.
|
|
4. Keep framework adapters, state, deployment, and product-specific behavior in this repository.
|
|
5. Record the boundary decision in `docs/DECISIONS.md`.
|
|
|
|
## 9. Knowledge Asset Workflow
|
|
|
|
For long-term reusable knowledge rules, see `docs/KNOWLEDGE_ASSET_RULES.md`.
|
|
|
|
When a rule, model map, schema explanation, workflow summary, or product context becomes stable enough to reuse across sessions, create or update a file under `knowledge_assets/`.
|
|
|
|
Do not leave durable knowledge only in temporary reports.
|
|
|
|
For repository-wide file identity rules, including canonical files, generated reports, review archives, and temporary files, see `docs/FILE_TAXONOMY.md`.
|