vassiliylakhonin.github.io

# vassiliylakhonin.github.io

<p align="left">
  <a href="https://github.com/vassiliylakhonin/vassiliylakhonin.github.io/actions/workflows/link-check.yml"><img src="https://img.shields.io/github/actions/workflow/status/vassiliylakhonin/vassiliylakhonin.github.io/link-check.yml?branch=main&style=for-the-badge" alt="CI"></a>
  <a href="https://vassiliylakhonin.github.io/"><img src="https://img.shields.io/badge/live-site-blue?style=for-the-badge" alt="Live site"></a>
  <a href="./LICENSE"><img src="https://img.shields.io/badge/license-MIT-green?style=for-the-badge" alt="License"></a>
  <a href="https://agenstry.com/agents/vassiliylakhonin.github.io"><img src="https://agenstry.com/badge/vassiliylakhonin.github.io.svg" alt="Agenstry grade"></a>
  <a href="https://agenstry.com/agents/vassiliylakhonin.github.io"><img src="https://agenstry.com/badge/vassiliylakhonin.github.io/protocol.svg" alt="A2A protocol version"></a>
</p>

Personal portfolio site of Vassiliy Lakhonin — I build evidence-discipline tooling for strategic-risk AI agents (Agenda Intelligence: an open-source skill portfolio plus deployed A2A workers and a public CIS counterparty EDD browser demo), grounded in donor compliance, audit readiness, and cross-border program delivery.

This repository is **two things at once**:

1. **The live site** at <https://vassiliylakhonin.github.io/> — human profile, recruiter snapshot, case studies, and a public browser demo of the CIS counterparty EDD worker.
2. **A reference implementation** of an AI-readable professional profile architecture: human pages plus machine-readable JSON endpoints, agent discovery (`llms.txt`, `agent-card.json`), recruiter routing, and an MCP server.

It is **not** a fork-and-go starter template — the content is personal. Other people are welcome to study the architecture and adapt it for their own profile.

## Why this architecture

Recent research on AI self-preferencing in algorithmic hiring suggests that LLM evaluators can favor resume text that resembles their own outputs, even when candidate quality is controlled. This repo treats that as a design constraint: publish multiple verified surfaces so humans, ATS systems, and recruiter agents can compare claims, evidence, role fit, and contact details instead of relying on one polished resume style.

See [`AGENTS.md`](./AGENTS.md) for the canonical rules any AI agent (Claude Code, Codex, recruiter LLMs) should follow when reading or editing this repo.

## Portfolio context

This site is the distribution surface for two workflow products awaiting external validation and a separately maintained four-repository strategic-risk stack.

Workflow products:

- **Corridor Bankability Analyst** (private preview, repository not yet public) — drafts evidence-structured corridor deliverables from bounded source packs for a named human to verify and sign: bankability screens, tariff and cost diagnostics, market-barrier analyses, country readiness notes, position papers, and market-entry readiness notes, exported to DOCX or print-ready PDF. Documents, not scores — no readiness verdict or go/no-go. Buyer, price, and paid continuation remain hypotheses until a real external case is completed. Public worked sample on two primary records: [Aktau Port bankability screen](https://vassiliylakhonin.github.io/aktau-bankability-screen-sample.html).
- [**GrantFlow**](https://github.com/vassiliylakhonin/grantflow) — produces human-reviewable grant proposal and evidence artifacts: a bid/no-bid record, a file-level draft assessment with a prioritized reviewer queue, a donor-aware first draft, an evidence-gap list, and `.docx` / `.xlsx` / ZIP exports. Two delivery paths — an operated pilot, or MCP / HTTP interfaces for teams embedding the workflow. Being tested case by case; the API and hosted demo are not demand evidence.

Strategic-risk stack:

- [**Agenda Intelligence MD**](https://github.com/vassiliylakhonin/agenda-intelligence-md) — deterministic evidence-packet linter for claim-backed AI output. The first-run workflow checks source references, declared quotes, lexical support, and unmatched numbers before human review; v1.4.0 (2026-07-22) exposes it to MCP clients as `check_evidence_packet`, with `create_brief` and `append_evidence` for contract-aware assembly. Older HTTP / A2A and vertical-worker surfaces remain available for compatibility; they are not the primary product narrative.
- [**Global Think Tank Analyst**](https://github.com/vassiliylakhonin/global-think-tank-analyst) — horizontal strategic-risk reasoning skill (method: Policy Risk Memo Architect).
- [**Central Asia + Caspian Hybrid Intelligence Skill**](https://github.com/vassiliylakhonin/central-asia-caspian-hybrid-intelligence-skill) — vertical regional / corridor-risk specialist for Central Asia and the Caspian.
- [**Gulf + Middle East Hybrid Intelligence Skill**](https://github.com/vassiliylakhonin/gulf-middle-east-hybrid-intelligence-skill) — vertical specialist for Iran sanctions, GCC banking / sovereign wealth, energy markets and maritime chokepoint risk.

The three reasoning repos now use the same handoff into Agenda Intelligence MD: memo → externally checkable claims + declared source IDs + supplied source text + optional verbatim quotes → deterministic packet check → human review. Each repo ships a synthetic packet, a local validator, and a CI check. Historical `analyze` / MCP evals remain compatibility evidence rather than proof of the current linter.

## What's in here

- Human-friendly profile site (GitHub Pages + Jekyll): `index.md`, `for-recruiters.md`, `profile.md`, role snapshots in `role-*.md`, case studies in `case-study-*.md`.
- Structured profile endpoints: `resume.json`, `skills.json`, `capabilities.json`, `availability.json`, `verification.json`, `recruiter.json`, `engage.json`, `evidence.json`.
- Agent discovery: `agent-card.json`, `agent-discovery.md`, `llms.txt` (short routing index) and `llms-full.txt` (complete inventory).
- Client setup page: `connect.md` — MCP install commands per client, the A2A call pattern, and what each surface may claim.
- Self-preference-aware recruiter routing: `candidate-match.json`, `agent-match.md`, `for-recruiters.md`.
- MCP server for recruiter / agent queries: `mcp/server.py` (runnable locally) plus a remote deployment live on Cloudflare Workers at `https://vassiliy-lakhonin-mcp.vassiliy-lakhonin.workers.dev/mcp` (streamable HTTP) — see `mcp-status.json`. Both implementations expose 16 tools, 19 attachable resources, and 5 prompts (`screen_for_role`, `check_claim`, `route_my_problem`, `brief_before_call`, `draft_outreach`). Worker source: `mcp/cloudflare-worker/`.
- Observability artifacts: `freshness.json`, `provenance.json`, `readiness.json`, `evals.json`, `authority.json`. Values are self-reported snapshots, not validated benchmarks.
- Analytics measurement plan: `docs/analytics-measurement-plan.md`.
- CI: link check, schema audit, observability snapshot refresh.

## Live entry points

- Site: <https://vassiliylakhonin.github.io/>
- Recruiter page: <https://vassiliylakhonin.github.io/for-recruiters.html>
- ATS resume (plain): <https://vassiliylakhonin.github.io/Vassiliy-Lakhonin_ATS-Resume.html>
- Agent card: <https://vassiliylakhonin.github.io/agent-card.json>
- A2A Agent Card: <https://vassiliylakhonin.github.io/.well-known/agent-card.json>
- A2A JSON-RPC endpoint: <https://agenda-intelligence-a2a.vassiliy-lakhonin.workers.dev/message/send>
- Agenstry provider listings: <https://agenstry.com/providers/Vassiliy%20Lakhonin>
- Kazakhstan / Middle Corridor Deal Risk Gate: <https://middle-corridor-deal-risk-gate-a2a.vassiliy-lakhonin.workers.dev>
- Kazakhstan Market Entry Readiness Gate: <https://kazakhstan-market-entry-readiness-a2a.vassiliy-lakhonin.workers.dev>
- CIS Secondary-Sanctions Exposure: <https://cis-secondary-sanctions-a2a.vassiliy-lakhonin.workers.dev> — [interactive demo](https://vassiliylakhonin.github.io/cis-secondary-sanctions.html)
- Agentic Interaction Trust Gate: <https://agentic-interaction-trust-a2a.vassiliy-lakhonin.workers.dev>
- Gulf Maritime Exposure Gate: <https://gulf-maritime-exposure-a2a.vassiliy-lakhonin.workers.dev>
- Agent Output Verification: <https://agent-output-verification-a2a.vassiliy-lakhonin.workers.dev>
- Resume JSON: <https://vassiliylakhonin.github.io/resume.json>
- MCP status: <https://vassiliylakhonin.github.io/mcp-status.json>

## Architecture

```mermaid
flowchart LR
  A[Markdown and JSON profile source] --> B[GitHub Pages site]
  A --> C[Machine-readable endpoints]
  C --> D[AI search and retrieval]
  C --> E[MCP Server]
  E --> F[Recruiter and agent clients]
  A --> G[CI audits and observability]
```

## Repository map

```text
.
├── AGENTS.md
├── index.md
├── for-recruiters.md
├── profile.md
├── resume.json
├── capabilities.json
├── evidence.json
├── availability.json
├── skills.json
├── verification.json
├── agent-card.json
├── agent-discovery.md
├── llms.txt
├── mcp/
│   ├── server.py
│   ├── cloudflare-worker/
│   ├── README.md
│   └── requirements.txt
├── scripts/
└── .github/workflows/
```

## Adapting the architecture for your own profile

If you want to reuse the pattern (not the content):

1. Read [`AGENTS.md`](./AGENTS.md) and [`docs/AI_HIRING_READINESS.md`](./docs/AI_HIRING_READINESS.md) to understand the model.
2. Copy the file structure (JSON endpoints + agent-card + llms.txt + role snapshots + MCP server) and replace every personal claim with your own evidence-backed content.
3. Keep the honesty rules: do not publish scores or "readiness" numbers without a methodology that traces back to a script in `scripts/`.
4. Run the local checks before publishing.

## Local checks

```bash
python3 scripts/geo_quick_audit.py
python3 scripts/schema_audit.py
python3 scripts/build_readiness_report.py
python3 scripts/build_freshness_report.py
python3 scripts/build_evals_report.py
python3 scripts/build_provenance_report.py
```

Optional CIS EDD source-freshness snapshot:

```bash
python3 scrip