yandex-wordstat-guide: Instructions file for Codex

AGENTS.md

yandex-wordstat-guide AGENTS.md is an instructions file for Codex, OpenCode from axelfreeman/yandex-wordstat-guide. It costs 2,038 tokens per session, scanned A, original, MIT.

Repository instructions for collecting Russian-language Yandex search-query statistics through the Yandex Search API. Yandex Wordstat is Yandex’s service for studying what people search for and how often.

In plain words
What is it for?
Use them to collect keyword phrases, search-volume data, Russian search trends, and inputs for SEO content generation.
Why use it?
They turn search data into structured output that an AI agent can use without manually working through the Wordstat website.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: positional $N argument; mentions AGENTS.md.

This is axelfreeman/yandex-wordstat-guide's own configuration. It tells Codex and OpenCode how to work on yandex-wordstat-guide itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything yandex-wordstat-guide configures →

Reuse

Borrowing it

Nothing to install: this file belongs to axelfreeman/yandex-wordstat-guide. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/axelfreeman/yandex-wordstat-guide/master/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/axelfreeman/yandex-wordstat-guide

Made for: Codex, OpenCode.

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ModelPer sessionOnce invoked
Fable 5.1 $0.02038 $0.02038
Opus 5 $0.01019 $0.01019
Sonnet 5 $0.00408 $0.00408
Haiku 4.5 $0.00204 $0.00204

Measured 8d ago against content hash 2046fc5d2d3e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

yandex-wordstat-guide AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 222 lines

How it starts

The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Yandex Wordstat Guide for AI Agents

A toolkit for AI agents to collect Yandex search query statistics programmatically. Use this repo to gather Russian-language search semantics, find trending topics, and feed structured keyword data into LLMs for SEO content generation — all without the manual Wordstat UI.

What this project is

Yandex Wordstat is the only source of real search volume data for the Russian-speaking internet (Runet). This project wraps the Yandex Search API v2 into Python scripts that an AI agent can invoke directly. The output is structured JSON — ready to pipe into DeepSeek, GPT, or Claude for content generation.

Quick start for AI agents

Prerequisites

# 1. Clone
git clone https://github.com/axelfreeman/yandex-wordstat-guide.git
cd yandex-wordstat-guide

# 2. Install deps
pip install -r requirements.txt   # only 'requests'

# 3. Set credentials
export WORDSTAT_API_KEY="AQVN..."       # Yandex Cloud API key
export WORDSTAT_FOLDER_ID="b1g..."      # 20-char folder ID — must be exactly 20 chars!

Your first collection

python3 scripts/collect.py "ремонт квартир" "дизайн интерьера"
# → semantic_results.json with deduplicated phrases sorted by search volume

What you can do with this

1. Collect search semantics (scripts/collect.py)

Takes seed phrases → expands each via topRequests API → deduplicates → sorts by volume.

python3 scripts/collect.py "keyword1" "keyword2" "keyword3"

Output (semantic_results.json):

{
  "collected_at": "2026-08-11T14:30:00",
  "total_phrases": 171,
  "requests_used": 12,
  "results": [
    {"phrase": "ремонт квартир под ключ", "count": 12450, "source": "ремонт квартир"},
    {"phrase": "дизайн интерьера квартиры", "count": 6720, "source": "дизайн интерьера"}
  ]
}

2. Find explosive trends (scripts/trending.py)

Discovers phrases with ≥200% month-over-month growth. For each seed, collects top-15 related phrases, then pulls 6-month history via dynamics API.

Read the full file on GitHub · 222 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 222 lines · 2,038 tokens per session scan A 2046fc5d2d3e

Subscribe to this mod's changes

yandex-wordstat-guide AGENTS.md is an instructions file published in the GitHub repository axelfreeman/yandex-wordstat-guide (34 stars, last pushed 17d ago), licensed MIT. It adds 2,038 tokens to every session, about $0.0102 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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