ds-content-perf

ds-content-perf is a skill for Claude Code from Dataslayer-AI/Marketing-skills. It costs 121 tokens per session (3,205 once invoked), scanned A, original, MIT.

A guide for measuring whether blog and other content attracts visitors, engages them, and leads to actions such as trial signups or paid accounts.

In plain words
What is it for?
Use it to compare content over time, find posts that drive conversions, assess audience fit, and decide what to write next.
Why use it?
It connects content activity to business results instead of judging articles only by page views.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: model in frontmatter.

Part of the dataslayer-marketing-skills plugin — 10 skills, 4 agents shipped together

Good fit Use it to compare content over time, find posts that drive conversions, assess audience fit, and decide what to write next.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dataslayer-ai/marketing-skills/ds-content-perf
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Dataslayer-AI/Marketing-skills --skill ds-content-perf
Clone the repo
git clone --depth 1 https://github.com/Dataslayer-AI/Marketing-skills

Made for: Claude Code.

Or install dataslayer-marketing-skills, the plugin that ships this one along with the rest of its 10 skills, 4 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ds-content-perf

README.md
[![agentmods](https://agentmods.dev/badge/skills/dataslayer-ai/marketing-skills/ds-content-perf/github.svg)](https://agentmods.dev/skills/dataslayer-ai/marketing-skills/ds-content-perf)
Your own site
<a href="https://agentmods.dev/skills/dataslayer-ai/marketing-skills/ds-content-perf"><img src="https://agentmods.dev/badge/skills/dataslayer-ai/marketing-skills/ds-content-perf/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ds-content-perf

Your own site · 80×15
<a href="https://agentmods.dev/skills/dataslayer-ai/marketing-skills/ds-content-perf"><img src="https://agentmods.dev/badge/skills/dataslayer-ai/marketing-skills/ds-content-perf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,205 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00121 $0.03205
Opus 5 $0.00060 $0.01603
Sonnet 5 $0.00024 $0.00641
Haiku 4.5 $0.00012 $0.00320

Measured 12d ago against content hash 09a0bdb3e52d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ds-content-perf 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 12d 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.

skills/ds-content-perf/SKILL.md · 358 lines

How it starts

The opening of the file, as written. The whole thing — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Content performance analysis (ds-content-perf)

You are a content strategist who connects content output to business outcomes. You do not measure success by pageviews. You measure it by whether content moves people through the funnel — from discovery to trial to paid. You separate content that looks good in a dashboard from content that actually drives the business.


Step 1 — Read context

Business context (auto-loaded): !cat .agents/product-marketing-context.md 2>/dev/null || echo "No context file found."

Pay particular attention to:

  • The primary conversion goal (trial signup, demo, etc.)
  • The audience (ICP) — informational content targeting the wrong audience is a common problem worth flagging
  • Any known editorial strategy (informational vs conversion-focused content)

If no context was loaded above, ask:

"What is the conversion event I should track — trial signups, demo requests, or something else? And do you have a target conversion rate for blog content?"

If the user passed a date range as argument, use it: $ARGUMENTS Default date range: last 90 days vs previous 90 days. Content performance needs more time than paid campaigns to show meaningful patterns.


Step 2 — Get the data

First, check if a Dataslayer MCP is available by looking for any tool matching *__natural_to_data in the available tools (the server name varies per installation — it may be a UUID or a custom name).

Path A — Dataslayer MCP is connected (automatic)

Important: always fetch current period and previous period as two separate queries. The MCP returns cleaner data when periods are split. Calculate % change yourself after receiving both.

Important: the MCP returns all rows regardless of any "top N" request. Request all data and filter/sort locally using bash/python after receiving the saved file.

Fetch in parallel (each as TWO queries — current period + previous period):

GA4:
  - All blog/content pages: sessions grouped by
    landingPagePlusQueryString AND sessionDefaultChannelGroup
    → This gives you both the page-level totals and the traffic source
      breakdown in a single query.

  - Conversions: sessions grouped by landingPagePlusQueryString AND
    eventName, filtered to pages containing /blog/.

Search Console:
  - All pages with impressions, clicks, CTR, average position
    filtered to pages containing /blog/

Read the full file on GitHub · 358 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. 12d ago First seen · 358 lines · 121 tokens per session scan A 09a0bdb3e52d

Subscribe to this mod's changes

ds-content-perf is a skill published in the GitHub repository Dataslayer-AI/Marketing-skills (23 stars, last pushed 5mo ago), licensed MIT. It adds 121 tokens to every session and 3,205 once invoked, about $0.0006 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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