85 lines
4.7 KiB
Markdown
85 lines
4.7 KiB
Markdown
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# Review Coordination Agent
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Agent 3 is available at `/review-workbench`. The local preview runs at
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`http://127.0.0.1:3012/review-workbench` with the API on loopback port 8012.
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The application reuses Agent 1 risk snapshots, identity configuration, SQLite
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storage, audit trail, and mini-openclaw's scoped AgentManager execution.
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## Workflow
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1. Create a coordination project from an existing risk run. Select its industry
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and complexity (1-5). Only one active coordination record per project is allowed.
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2. Configure reviewers with industries, capacity, outside workload, availability,
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and project exclusions. The recommendation ranks eligible people using industry
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matching (40 points) and remaining capacity after assignment (up to 60 points).
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Local workload is the sum of assigned active project complexity. Capacity and
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outside workload use the same units. These are preview heuristics, not approved
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Xingbang assignment policy. An administrator confirms the local assignment.
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3. Convert findings into follow-up tasks with an owner and due date, or record
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a reviewer's evidence-based disposition. Material submission does not close a
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task. Inspection must precede reviewer confirmation. A reviewer can reopen it.
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4. Record the proposal: CNY ten-thousands, months, annual percentage rate, deposit
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percentage, and guarantee conditions. Each actual change stores old/new values
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and creates affected review items. Decimal-equivalent inputs are not changes.
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5. Confirm pending risks, tasks and change reviews before department review,
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committee preparation, or completion. A proposal must also be recorded.
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6. Inspect the current briefing, export text, or request an AI briefing.
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Proposal changes during department review or committee preparation return the
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project to financial analysis. Updating to a later risk snapshot for the same
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project preserves previous snapshots, invalidates applicability of old risk
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confirmations, and creates data/report review tasks. Open tasks remain open.
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## Human Authority
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- Administrator: people configuration, local assignment, task preparation,
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inspections and proposal recording.
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- Reviewer: risk disposition, task resolution/reopening, change confirmation,
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and progression through final review stages; also prepares tasks and proposals.
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- Customer manager: sees authorized project records and submits material references.
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- Loopback-only preview: all operations enabled for demonstration.
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The current roles reuse the existing application roles. Secretary, assigned main
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reviewer and department-head identity mapping still needs formal organization
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integration. The workspace records local responsibilities; it does not assign or
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approve projects in ERP. Configure authentication using `RISK_AGENT_GUIDE.md`.
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## Agent Execution
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The optional AI briefing uses `risk.local_model` -> `invoke_risk_task` ->
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`AgentManager.invoke_scoped` with only authorized snapshot-reading tools and the
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`review_coordination/SKILL.md` native skill. It cannot assign, close tasks, execute
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SQL, or change reports. Missing model configuration returns a clear error without
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changing the project. A briefing is visibly stale after another project update.
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Tests run the real agent/tool loop with a deterministic test model; a production
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local model has not been exercised in this environment.
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## Current Integration Boundaries
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- Reviewer information and workload are manually configured, not live ERP data.
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- Material submissions record ERP identifiers or file locations. There is no
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file upload, attachment retrieval or content inspection in this version.
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- Change impacts are conservative deterministic review checklists. They do not
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perform financial recalculation or automatically rewrite Agent 2 reports.
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- Source updates select a later existing Agent 1 run; they do not poll ERP.
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- The briefing export is text, not the formal committee document template.
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- This does not implement experience retrieval from Agent 2, reminder delivery,
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automatic assignment, or formal approval writeback.
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- Sample people and tasks created by browser verification are explicitly labeled
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as examples. They are stored locally and can be used to try the workflow.
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## Verification
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```powershell
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python -m unittest discover -s backend -p "test_coordination_agent.py"
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python -m unittest discover -s backend -p "test_risk_agent*.py"
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python -m unittest discover -s backend -p "test_report_agent.py"
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python -m unittest discover -s backend -p "test_risk_core.py"
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npx tsc --noEmit
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node verify-coordination-agent.cjs
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```
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The browser script uses the running preview servers and creates labeled demo
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records. It checks project intake, people, assignment, material submission, plan
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changes and impacts, briefing download, and layouts at 1440, 1024 and 390 pixels.
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