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 scrollmark/socialgpt-mcp --skill content-performance-auditgit clone --depth 1 https://github.com/scrollmark/socialgpt-mcpWrote 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/scrollmark/socialgpt-mcp/content-performance-audit)<a href="https://agentmods.dev/skills/scrollmark/socialgpt-mcp/content-performance-audit"><img src="https://agentmods.dev/badge/skills/scrollmark/socialgpt-mcp/content-performance-audit/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/scrollmark/socialgpt-mcp/content-performance-audit"><img src="https://agentmods.dev/badge/skills/scrollmark/socialgpt-mcp/content-performance-audit.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 | $0.00118 | $0.00888 |
| Opus 5.5 | $0.00047 | $0.00355 |
| Sonnet 5.5 | $0.00024 | $0.00178 |
| Haiku 4.5 | $0.00012 | $0.00089 |
Grade A, and why
content-performance-audit 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.
How it starts
The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Performance Audit
Turn a creator's own post history into a ranked, statistically-tested answer to "what actually drives my views?" — instead of guessing, you measure.
This skill pairs with the SocialGPT MCP server (https://mcp.gpt.social/mcp).
The MCP provides the data; this skill provides the deterministic analysis and a
shareable report. If the SocialGPT tools below aren't available, the user needs
to connect the MCP first: https://gpt.social/integrations/mcp
When to use
Trigger on requests like: "what drives my views?", "what's working on my account?", "what should I post more of?", "do a performance audit", "why did some videos pop and others flop?"
Workflow
-
Confirm access. Make sure the SocialGPT MCP tools are connected. If
list_videosisn't available, point the user to the connect page above and stop. -
Pull the data. Call the MCP tool:
list_videos(limit=50, sort="recent", include_analysis=false)To audit a single connected account, first call
list_accounts()and pass itsaccount_id. Save the raw JSON the tool returns to a file namedvideos.jsonin the working directory (the whole{"videos": [...]}envelope is fine — the script handles it). -
Run the analysis (it has no third-party dependencies):
python scripts/analyze.py videos.jsonThe script reads
videos.json, runs the tests, prints a Markdown summary to stdout, and writescontent-performance-report.html. -
Relay the result. Present the Markdown summary the script printed, then offer the user the generated
content-performance-report.htmlto download / open (on Claude.ai it appears as a downloadable file).
What the script does
For every video with a usable view count (Instagram posts showing 0 plays are treated as missing, since IG hides reel plays), it tests each factor against view count and ranks them by effect size and p-value:
- Continuous factors (video length, engagement rate) → Pearson correlation on log-views, with a real two-sided p-value.
- Categorical factors (platform, day of week, time of day, sequel vs. standalone) → Kruskal-Wallis rank test, robust to the heavy-tailed view distribution.
What ships with it
3 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.
- 2mo ago First seen · 83 lines · 118 tokens per session scan A 5eb53bd2ed47
content-performance-audit is a skill published in the GitHub repository scrollmark/socialgpt-mcp (10 stars, last pushed 1mo ago), licensed MIT. It adds 118 tokens to every session and 888 once invoked, about $0.0005 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 2026-08-31.
content-performance-audit compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| content-performance-auditscrollmark/socialgpt-mcp | Skill | 10 | 1mo ago | MIT | A | 118 | Claude Code, Codex |
| 9router-sttdecolua/9router | Skill | 32k | 9d ago | MIT | A | 63 | Claude Code, Codex |
| 9router-videodecolua/9router | Skill | 32k | 9d ago | MIT | A | 74 | Claude Code, Codex |
| 9router-web-fetchdecolua/9router | Skill | 32k | 9d ago | MIT | A | 67 | Claude Code, Codex |
| 9router-web-searchdecolua/9router | Skill | 32k | 9d ago | MIT | A | 74 | Claude Code, Codex |
| 9router-ttsdecolua/9router | Skill | 32k | 9d ago | MIT | A | 70 | Claude Code, Codex |
| 9routerdecolua/9router | Skill | 32k | 9d ago | MIT | A | 84 | Claude Code, Codex |