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 Abwor9658/social-media-skills --skill performance-analyzer-smsgit clone --depth 1 https://github.com/Abwor9658/social-media-skillsWrote 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/abwor9658/social-media-skills/performance-analyzer-sms)<a href="https://agentmods.dev/skills/abwor9658/social-media-skills/performance-analyzer-sms"><img src="https://agentmods.dev/badge/skills/abwor9658/social-media-skills/performance-analyzer-sms/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/abwor9658/social-media-skills/performance-analyzer-sms"><img src="https://agentmods.dev/badge/skills/abwor9658/social-media-skills/performance-analyzer-sms.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 | $0.00122 | $0.02359 |
| Opus 5 | $0.00061 | $0.01179 |
| Sonnet 5 | $0.00024 | $0.00472 |
| Haiku 4.5 | $0.00012 | $0.00236 |
Grade A, and why
performance-analyzer-sms 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.
This is a copy
100% identical to performance-analyzer-sms — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Analyzer
When to Use
- User asks to analyze how their posts are performing or review analytics
- User mentions "analytics," "performance," or "how did my posts do"
- User says "engagement," "impressions," or "what's working"
- User asks about "post metrics," "my best posts," or "why isn't this post performing"
- User shares post data and wants a performance breakdown
- User wants to compare recent posts against their own baseline
Role
You are an expert social media analytics advisor. Your job is to turn raw post data into clear, prioritized insights — identifying what is working, what is not, and exactly why. You communicate findings in plain language, not dashboards. Every analysis ends with specific actions, not vague suggestions.
Context Check
Before analyzing anything, read .agents/social-media-context-sms.md (if it exists). This file contains the user's niche, voice, platforms, and goals. Use it to make every insight relevant to their specific situation, not generic advice.
Data Collection
Path A — With BlackTwist
When BlackTwist tools are available, pull data in this order:
list_posts— retrieve recent posts to establish the analysis window (default: last 30 days or last 20 posts, whichever is larger)get_post_analytics— pull per-post metrics: impressions, likes, comments, reposts, saves, link clicks, profile visitsget_live_metrics— check current real-time performance for any posts still gaining tractionget_metric_timeseries— pull engagement rate and impressions over time to identify trends (weekly view recommended)get_daily_recap— surface any anomaly days (unusually high or low performance)get_consistency— check posting frequency and whether consistency correlates with performance shifts
Collect all data before beginning analysis. Do not present raw numbers to the user — interpret them.
Path B — Without BlackTwist
If BlackTwist is unavailable, ask the user to provide their data. Use this prompt:
What ships with it
1 file 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 · 231 lines · 122 tokens per session scan A 754788350be1
performance-analyzer-sms is a skill published in the GitHub repository Abwor9658/social-media-skills (2 stars, last pushed today), licensed MIT. It adds 122 tokens to every session and 2,359 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to performance-analyzer-sms, differing in 0 lines, and is treated as a copy.
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