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.
npx skills add KirKruglov/claude-skills-kit --skill content-performance-reportergit clone --depth 1 https://github.com/KirKruglov/claude-skills-kitWrote 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.
[](https://agentmods.dev/skills/kirkruglov/claude-skills-kit/content-performance-reporter)<a href="https://agentmods.dev/skills/kirkruglov/claude-skills-kit/content-performance-reporter"><img src="https://agentmods.dev/badge/skills/kirkruglov/claude-skills-kit/content-performance-reporter/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.
<a href="https://agentmods.dev/skills/kirkruglov/claude-skills-kit/content-performance-reporter"><img src="https://agentmods.dev/badge/skills/kirkruglov/claude-skills-kit/content-performance-reporter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00141 | $0.01945 |
| Opus 5 | $0.00071 | $0.00972 |
| Sonnet 5 | $0.00028 | $0.00389 |
| Haiku 4.5 | $0.00014 | $0.00194 |
Grade A, and why
content-performance-reporter 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Performance Reporter
This skill compiles CSV analytics exports from content platforms into a structured narrative weekly report — what worked, what didn't, the pattern behind top performers, and concrete recommendations for next week. Designed for marketers, SMM managers, and content creators who need readable editorial insight, not another dashboard.
Input:
- One or more CSV files from analytics platforms in the Cowork workspace (Instagram, YouTube, Google Analytics, LinkedIn, TikTok, Facebook, Twitter/X)
Output:
- Markdown report: per-platform metrics table, Top 3 / Bottom 3 posts, narrative What Worked / What Didn't, Pattern of the Week, and 1–2 actionable recommendations
Language Detection
Detect the user's language from their message:
- If Russian (or contains Cyrillic): respond in Russian
- If English (or other Latin-script language): respond in English
- If ambiguous: respond in the language of the trigger phrase used
Instructions
Step 1: Locate Files
-
Identify CSV files from the user's message
- If a filename or path is provided: use it directly
- If no file specified: scan the Cowork workspace folder for CSV files with analytics-related names (metrics, analytics, insights, export, report, stats, instagram, youtube, ga4, linkedin, tiktok, facebook, twitter)
- If no CSV files found: stop and report — "No analytics CSV files found. Upload your platform export and try again."
-
For each file: detect the platform by matching column headers against known patterns (see Platform Detection table below)
- If platform cannot be identified: mark as "Unknown platform" and continue with generic mode
Step 2: Extract Metrics
For each file, extract:
- Date / period (if present)
- Reach / impressions / views metrics
- Engagement metrics: Likes, Comments, Shares, Saves, Reactions, Engagement Rate
- Traffic metrics: Clicks, CTR, Link Clicks
- Platform-specific: Watch Time (YouTube), Follower Growth, Profile Visits
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 181 lines · 141 tokens per session scan A 74e3cb084880
content-performance-reporter is a skill published in the GitHub repository KirKruglov/claude-skills-kit (18 stars, last pushed 1mo ago), licensed MIT. It adds 141 tokens to every session and 1,945 once invoked, about $0.0007 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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