Marketing-skills: Instructions file for Claude Code

CLAUDE.md

Marketing-skills CLAUDE.md is an instructions file for Claude Code from Dataslayer-AI/Marketing-skills. It costs 608 tokens per session, scanned A, original, MIT.

Repository instructions for a collection of marketing-analysis skills that use live advertising and analytics data or data pasted by the user.

In plain words
What is it for?
Use them when developing or maintaining these marketing skills, following their required file format, reusing shared data-processing utilities, and keeping subagent outputs limited to data.
Why use it?
They explain the project structure and conventions, including where skills, agents, scripts, tests, reports, and user-specific business context belong.

Instructions file for Claude Code

Written for Claude Code: ${CLAUDE_SKILL_DIR} variable. Also seen: mentions CLAUDE.md; mentions subagents; mentions Claude Code.

This is Dataslayer-AI/Marketing-skills's own configuration. It tells Claude Code how to work on Marketing-skills 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 Marketing-skills configures →

Reuse

Borrowing it

Nothing to install: this file belongs to Dataslayer-AI/Marketing-skills. 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/Dataslayer-AI/Marketing-skills/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/Dataslayer-AI/Marketing-skills

Made for: Claude Code.

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README.md
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Per session 608 This file is loaded in full into every session.
When invoked 608 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 $0.00608 $0.00608
Opus 5 $0.00304 $0.00304
Sonnet 5 $0.00122 $0.00122
Haiku 4.5 $0.00061 $0.00061

Measured 9d ago against content hash 1179e23d065d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

Marketing-skills 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 9d 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 · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CLAUDE.md — Project conventions for Marketing-skills

What this repo is

A collection of Claude Code skills for marketing analysis. Skills work in two modes: automatic (with the Dataslayer MCP fetching live data from Google Ads, Meta, LinkedIn, GA4, Search Console, Stripe, and 50+ platforms) or manual (user pastes CSV/JSON data). Same analysis engine either way.

Repo structure

skills/          → Each subfolder is a skill (SKILL.md + optional scripts/)
agents/          → Each .md file is a subagent used by ds-brain
scripts/         → Shared utilities (ds_utils.py) and tests
reports/         → Generated PDFs (gitignored, local only)
.agents/         → Business context file (gitignored, user-specific)

Key conventions

  • SKILL.md format: Frontmatter (name, description, model, allowed-tools) followed by Step 1–4 sections, Tone rules, Related skills. See CONTRIBUTING.md.
  • Subagents return data only. No interpretation, no recommendations. The orchestrator (ds-brain) or standalone skill handles synthesis.
  • All data processing goes through scripts/ds_utils.py. Never write inline calculation scripts in SKILL.md files. ds_utils functions are tested (113 tests in test_ds_utils.py).
  • Use ${CLAUDE_SKILL_DIR} for file references — never hardcode paths.
  • Use !cat ... || echo "..."` for context injection in Step 1.
  • Date ranges: Skills and their corresponding subagents must use the same default date range. Currently: paid=30d, organic=28d, content=90d, retention=60d (cancellations) / 30d (charges).

Running tests

python scripts/test_ds_utils.py

QA tools

  • /ds-lint — Validates all SKILL.md and agent files against the spec
  • /ds-eval — Tests triggering accuracy with cases from eval/triggering-tests.yaml
  • /ds-audit — Cross-skill consistency review (description overlap, format, features)

MCP tool naming

Skills use wildcard patterns in allowed-tools: mcp__*__natural_to_data, mcp__*__check_task_id, etc. This matches any MCP server name — whether it's a UUID (auto-generated) or a custom name like "dataslayer". No user configuration needed.

Read the full file on GitHub · 62 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. 9d ago First seen · 62 lines · 608 tokens per session scan A 1179e23d065d

Subscribe to this mod's changes

Marketing-skills CLAUDE.md is an instructions file published in the GitHub repository Dataslayer-AI/Marketing-skills (22 stars, last pushed 5mo ago), licensed MIT. It adds 608 tokens to every session, about $0.0030 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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