AI Automation Consultant Delivery Kit
ClientDeliveryKitAgent is a client-facing workflow demo for turning synthetic client intake into pain point diagnosis, automation opportunity scorecards, useful signals, recommended actions, and public-safe delivery reports.
It is local-first, synthetic demo-only, and public-safe. It does not process real client data, connect real connectors, collect credentials, upload files, or execute real automation actions. The project is managed as a local spoke through AgentHubControlCenter and can be opened locally at:
http://localhost:8535
- Checkpoint:
CLIENTDELIVERYKIT-011-PROFILE-PIN-OR-MAINTAIN-SHOWCASE-DECISION-COMPLETE - Mode: local demo scoring, public-safe report export, and Streamlit dashboard
- Data: synthetic demo data only
- Execution: local dashboard view, object generation, and public-safe local report export only; no real automation actions
- Connector status: planned only
- GitHub status: live public showcase verified at
https://github.com/CHENXJC/ClientDeliveryKitAgent - Portfolio status:
recommend pinif a GitHub profile slot is available; otherwise maintain showcase as an AgentHub spoke
This project fills the portfolio gap between technical AgentOps dashboards and practical client delivery materials. It is intended to show how a business-oriented AI automation consultant can structure intake, diagnose operational pain, score automation opportunities, and prepare a public-safe delivery report.
- Client Intake
- Business Context Extraction
- Pain Point Diagnosis
- Workflow Bottleneck Mapping
- Automation Opportunity Scoring
- Useful Signals
- Recommended Actions
- Delivery Report / Proposal Summary
- AgentHubControlCenter Integration
client_intake: represented byClientIntakebusiness_context: represented byBusinessContextpain_point_diagnosis: implemented inclient_delivery_kit/pain_point_engine.pyworkflow_mapping: represented through pain point workflow areasautomation_opportunity_scoring: implemented inclient_delivery_kit/scoring_engine.pyuseful_signals: implemented inclient_delivery_kit/useful_signals.pyrecommendation_engine: implemented inclient_delivery_kit/recommendation_engine.pydelivery_report_builder: implemented inclient_delivery_kit/report_builder.pystreamlit_dashboard: implemented inapp.pyandclient_delivery_kit/dashboard_views.pyagenthub_export: currently summary object onlyconnector_readiness: planned only
CLIENTDELIVERYKIT-002 adds a deterministic local scoring engine that can:
- load synthetic JSON samples from
sample_data/ - validate demo-only client intake, business context, and workflow pain points
- diagnose workflow bottlenecks
- score automation opportunities using transparent weighted rules
- produce AgentHub-ready useful signal objects
- produce text-only recommended action objects
- build a public-safe delivery summary object without writing a full report
CLIENTDELIVERYKIT-003 adds a report builder that converts the demo DeliverySummary into:
- Markdown report:
outputs/public_reports/clientdeliverykit_demo_report.md - JSON report:
outputs/public_reports/clientdeliverykit_demo_report.json - CSV scorecard:
outputs/public_reports/clientdeliverykit_opportunity_scorecard.csv
All report artifacts include public-safe disclaimers and are generated only from synthetic demo data. The exporter rejects paths outside outputs/public_reports/, rejects outputs/private/, and does not connect external systems.
CLIENTDELIVERYKIT-004 adds a local Streamlit dashboard at:
http://localhost:8535
The dashboard shows Overview, Client Snapshot, Pain Point Diagnosis, Opportunity Scorecard, Useful Signals, Recommended Actions, Report Export, and AgentHub Integration. It does not provide file upload, credential input, OAuth, real connector, or real action execution.
Public showcase screenshots are captured under docs/images/. Representative
README preview images:
Full screenshot inventory:
01_dashboard_overview.png02_client_snapshot.png03_pain_point_diagnosis.png04_opportunity_scorecard.png05_useful_signals.png06_recommended_actions.png07_report_export.png08_agenthub_integration.png
Screenshots must use the synthetic dashboard only and must not show terminal secrets, private outputs, credential forms, or real customer data.
- Discovery summary
- Client pain point map
- Automation opportunity scorecard
- Recommended workflow improvements
- Risk and approval notes
- Suggested next steps
- Public-safe delivery report template
The project is discoverable by AgentHubControlCenter through agent_manifest.json. Future outputs should be convertible into useful signals, Action Center cards, report export sections, and connector readiness reviews.
All future real send, write, customer-data, or external-system actions must pass a connector readiness review and an approval gate before implementation.
ClientDeliveryKitAgent is now a local AgentHub spoke project. AgentHubControlCenter discovers this project through:
F:\AIProjects\ClientDeliveryKitAgent\agent_manifest.json
Current AgentHub status:
- Manifest status: valid local manifest
- Role in AgentHub: client-facing delivery workflow spoke
- Dashboard URL:
http://localhost:8535 - GitHub status: live public showcase verified at
https://github.com/CHENXJC/ClientDeliveryKitAgent - Public-safe status: synthetic demo-only
- Next note: maintain showcase; manual profile pin is optional if a slot is available
The files under sample_data/ use fictional demo-only information for "Demo Local Services Co." They contain no real customer information and are intended only for local planning, UI prototypes, and public-safe documentation.
The full generated demo report stays under outputs/public_reports/ and is not
intended to be embedded directly in the README. A compact public-safe summary is
available at docs/SAMPLE_DELIVERY_REPORT_SUMMARY.md.
From this project folder:
python -m json.tool agent_manifest.json
python -m json.tool agent_contract.json
python -m json.tool sample_data\demo_client_intake.json
python -m json.tool sample_data\demo_business_context.json
python -m json.tool sample_data\demo_workflow_pain_points.json
python -m pytest
python -m compileall .
python -m streamlit run app.py --server.port 8535The test suite covers schema parsing, demo loader safety, validators, scoring, useful signals, recommended actions, and public summary counts. Report tests cover Markdown disclaimers, JSON structure, CSV scorecard rows, safe path export, private output rejection, external path rejection, and end-to-end artifact generation. Dashboard tests cover dashboard data, required page sections, public-safe labels, and absence of upload or credential input fields.
ClientDeliveryKitAgent/
README.md
PROJECT_STATUS.md
agent_manifest.json
agent_contract.json
requirements.txt
client_delivery_kit/
sample_data/
outputs/
docs/
tests/
- Demo-mode only in the current stage.
- No real customer records.
- No real external connectors.
- No automatic send, write, delete, publish, or account actions.
- No client workflow execution.
command_templatevalues are display text only.- Future connector work must use approval gates before any real account or customer-data operation.
CLIENTDELIVERYKIT-002: Core data schema and scoring engine completeCLIENTDELIVERYKIT-003: Public-safe delivery report builder completeCLIENTDELIVERYKIT-004: Streamlit consultant dashboard completeCLIENTDELIVERYKIT-005: AgentHub import and showcase prep completeCLIENTDELIVERYKIT-006: Public showcase screenshots and GitHub prep completeCLIENTDELIVERYKIT-007: GitHub repo creation decision completeCLIENTDELIVERYKIT-008: Screenshot capture and showcase asset review completeCLIENTDELIVERYKIT-009: GitHub public repo first commit completeCLIENTDELIVERYKIT-010: Live showcase verification and AgentHub published status sync completeCLIENTDELIVERYKIT-011: Profile pin and maintain-showcase decision complete


