Verified / Plausible / Judgment / Unknown), trace risk-transmission channels (banking, payments, routing, ownership, corridors), and produce role-based implications instead of regional essays.AGENTS.md (project rules: identity, honesty, evidence, naming, definition of done).skills/codex/SKILL.md, skills/claude/SKILL.md, skills/openclaw/SKILL.md.scripts/validate_skills.py — checks structure, required phrases, forbidden determinative claims, and code-fence balance. Does not validate factuality of any output.STATUS.md and evals/self-adversarial-review.md.docs/companion-patterns.md.Generic LLMs produce broad, fluent commentary on Central Asia and the Caspian: high-level country narration, vague "monitor sanctions" advice, no transmission mechanism, no actor incentives, no trigger points, no evidence boundaries.
That output is not decision-useful for analysts, banks, fintechs, investors, logistics operators, or energy teams that actually have exposure to the region.
A skill needed to be small enough to attach to any capable agent and strict enough to actually change the shape of regional analysis — without becoming a framework, screening tool, or compliance product.
Most AI-generated regional analysis on Central Asia and the Caspian is fluent but decision-light. It rarely traces how a sanction, regulation, or corridor shift transmits into bank exposure, payment routing, ownership chains, or logistics costs. It rarely separates what is verified from what is plausible inference, and it rarely names the trigger points that would update the view.
That is fine for background reading. It is weak for sanctions-exposure decisions, AML escalation, banking risk, corridor planning, energy and minerals exposure, or any regional risk decision that has to be defensible.
AGENTS.md as a canonical project-rules spec: identity, honesty, evidence, naming hierarchy, and a definition of done with two explicit bars (structural and substantive).Verified / Plausible / Judgment / Unknown labels;scripts/validate_skills.py as a structural validator (required phrases, forbidden determinative claims, code-fence balance). Made it explicit that this validator does not check factuality.evals/self-adversarial-review.md) listing the skill's own failure modes and known weaknesses, instead of marketing it as solved.docs/companion-patterns.md describing how this skill composes with Global Think Tank Analyst (broader memo workflow) and Agenda Intelligence MD (validation, evidence audit, scoring) — illustrative, with a clear pointer to those repos for current interfaces.Verified, Plausible, Judgment, and Unknown visibly in every output.This skill is the vertical specialist layer in a three-repo portfolio designed to compose:
This repo does not duplicate either neighbor. The broader memo workflow lives in Global Think Tank Analyst; validation tooling lives in Agenda Intelligence MD; this repo carries regional reasoning depth.
The skill is small enough to attach to any capable agent, and strict enough to change the shape of regional output. The contract does not ask the model to sound regionally smart; it asks the model to trace mechanism, label evidence, name the trigger, and say what role the implication is for.
That is the part most generic Central Asia / Caspian commentary misses.
Excerpt from a flagship example in the repo, condensed for this page. Full memo with full transmission mechanism, exposure map, leverage shifts, and triggers: examples/fintech-sanctions-routing.md. Evidence mode: reasoning-only — operational use requires source-backed verification through official sanctions lists and qualified professional review.
User question: "We are a fintech operating between Kazakhstan and Uzbekistan, with cross-border flows touching Caspian-connected trade routes (Aktau, Baku, Middle Corridor). What are our sanctions, AML, banking and routing risks over the next 6–12 months, and what should we do about them?"
Before — generic regional commentary:
Central Asia faces increased scrutiny over potential sanctions circumvention. Fintechs operating in Kazakhstan and Uzbekistan should ensure robust compliance programs, conduct thorough KYC, and monitor regulatory developments. Working with reputable banking partners and maintaining transparency with regulators is essential.
Fluent regional commentary. Does not say how the risk transmits, who gets affected, or what would update the view.
After — with the Central Asia + Caspian skill attached:
Judgment): For an SME-facing cross-border fintech in KZ / UZ with Middle Corridor exposure, the dominant risk over 6–12 months is secondary-sanctions and de-risking pressure transmitting through correspondent banking, amplified by routing and ownership opacity in re-export and dual-use flows. The risk is not primarily designation — it is losing or having to re-price USD / EUR rails, and counterparty contamination.Unknown here (requires direct screening); local AML EDD tightening = Plausible, requires verification; correspondent de-risking dynamic = Judgment.The skill does not screen sanctions, retrieve sources, or verify facts. It forces the agent to reason mechanism-first, label what is Verified / Plausible / Judgment / Unknown, and produce role-specific implications instead of regional essays.
AGENTS.md, skills/codex/SKILL.md, skills/claude/SKILL.md, skills/openclaw/SKILL.md, STATUS.md).scripts/validate_skills.py).This project demonstrates how I think about useful agent infrastructure for high-stakes regional reasoning: small reusable layers, mechanism-first contracts, honest evidence discipline, and outputs aimed at sanctions, banking, corridor, energy, and political-economy decisions — composed cleanly with a horizontal skill and a separate infrastructure layer instead of bundling everything into one repo.
Author: Vassiliy Lakhonin