seo-dfs-cc: Instructions file for Claude Code

CLAUDE.md

seo-dfs-cc CLAUDE.md is an instructions file for Claude Code from adamkristopher/seo-dfs-cc. It costs 1,616 tokens per session, scanned A, original, MIT.

A Python toolkit for researching search keywords through the DataForSEO service, which provides data about how people search online.

In plain words
What is it for?
Use it to request keyword ideas, search metrics, search intent, Google or YouTube rankings, and trend data, with results saved as JSON and summaries.
Why use it?
It removes the need to manually gather search volume, competition, rankings, trends, and related keyword information from several sources.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md.

This is adamkristopher/seo-dfs-cc's own configuration. It tells Claude Code how to work on seo-dfs-cc 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 seo-dfs-cc configures →

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /Users/adamcarter/Desktop/SEO/.

Reuse

Borrowing it

Nothing to install: this file belongs to adamkristopher/seo-dfs-cc. 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/adamkristopher/seo-dfs-cc/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/adamkristopher/seo-dfs-cc

Made for: Claude Code.

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README.md
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Per session 1,616 This file is loaded in full into every session.
When invoked 1,616 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.01616 $0.01616
Opus 5.5 $0.00646 $0.00646
Sonnet 5.5 $0.00323 $0.00323
Haiku 4.5 $0.00162 $0.00162

Measured 2mo ago against content hash 67094fe9d022, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

seo-dfs-cc CLAUDE.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 2mo 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.

CLAUDE.md · 200 lines

How it starts

The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DataForSEO Keyword Research Toolkit

Overview

This is a Python toolkit for keyword research using the DataForSEO API. Claude executes research functions on your behalf and saves structured results to JSON files, then creates human-readable summary documents for decision-making.

Project Structure

/Users/adamcarter/Desktop/SEO/
├── .env                      # API credentials (DO NOT COMMIT)
├── main.py                   # High-level convenience functions
├── config/
│   └── settings.py           # Configuration and defaults
├── core/
│   ├── client.py             # DataForSEO API client (singleton)
│   └── storage.py            # Auto-save results to JSON
├── api/
│   ├── keywords_data.py      # Search volume, CPC, competition
│   ├── labs.py               # Suggestions, difficulty, intent
│   ├── serp.py               # Google/YouTube rankings
│   └── trends.py             # Google Trends data
└── results/
    ├── keywords_data/        # Raw JSON from Keywords Data API
    ├── labs/                 # Raw JSON from Labs API
    ├── serp/                 # Raw JSON from SERP API
    ├── trends/               # Raw JSON from Trends API
    └── summary/              # Human-readable markdown summaries

How to Use (Prompting Claude)

Basic Research Requests

Just tell Claude what you want to research:

  • "Research keywords for [topic]"
  • "Get YouTube keyword data for [video idea]"
  • "Find keyword suggestions for [seed keyword]"
  • "Analyze competitor [domain.com]"
  • "What's trending in [category]"

Specific Function Requests

For more control, request specific functions:

  • "Run get_keyword_suggestions for 'AI website builders'"
  • "Get get_youtube_serp for these keywords: [list]"
  • "Use get_bulk_keyword_difficulty on [keywords]"

Summary Requests

After running research, ask for summaries:

  • "Create a summary of those results in /results/summary"
  • "Put the results in a document named [specific-name].md"
  • "Summarize the data so I can make decisions"

Read the full file on GitHub · 200 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. 2mo ago First seen · 200 lines · 1,616 tokens per session scan A 67094fe9d022

Subscribe to this mod's changes

seo-dfs-cc CLAUDE.md is an instructions file published in the GitHub repository adamkristopher/seo-dfs-cc (11 stars, last pushed 11mo ago), licensed MIT. It adds 1,616 tokens to every session, about $0.0065 per session on Opus 5.5. 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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