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 reymerekar7/rm-skills --skill x-scannergit clone --depth 1 https://github.com/reymerekar7/rm-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/reymerekar7/rm-skills/x-scanner)<a href="https://agentmods.dev/skills/reymerekar7/rm-skills/x-scanner"><img src="https://agentmods.dev/badge/skills/reymerekar7/rm-skills/x-scanner/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/reymerekar7/rm-skills/x-scanner"><img src="https://agentmods.dev/badge/skills/reymerekar7/rm-skills/x-scanner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 30 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 55 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00099 | $0.01274 |
| Opus 5 | $0.00049 | $0.00637 |
| Sonnet 5 | $0.00020 | $0.00255 |
| Haiku 4.5 | $0.00010 | $0.00127 |
Grade A, and why
x-scanner 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.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
X/Twitter Scanner
What This Does
Uses xAI's Grok API with the built-in x_search tool to scan X/Twitter for recent posts
from AI-focused accounts. Grok has native access to X data, so one API call handles search,
filtering, and summarization. No separate Twitter API credentials needed.
The scan produces a structured digest tagging launches, tools worth trying, learning material, build ideas, and content angles — with a coverage check so your must-watch accounts never silently drop out.
Setup
The script reads the xAI API key from the environment first, then falls back to a .env
file (it walks up the directory tree to find one). Either works:
export XAI_API_KEY=your_xai_api_key_here
# or add to a .env file at your project root:
# XAI_API_KEY=your_xai_api_key_here
Get an API key from https://x.ai/api. No external Python packages are needed — the script uses the standard library only.
Configuring Who You Track — watchlist.json
Accounts live in watchlist.json next to the scripts/ folder. Edit that file, not the
script, to track whoever you want. It has two parts:
must_surface_handles— accounts the scan always tries to cover. If one is missed on the first pass, the scanner automatically re-scans just those handles and merges them in. A coverage footer reports how many were surfaced.groups— everyone else, organized into named buckets (AI labs, builders, news, etc.). Each group is scanned together, and grouped scans kick in as a fallback if a broad pass comes back thin. Handles can be plain strings or{ "handle": "...", "note": "..." }objects — notes are just for your own reference.
If watchlist.json is missing or invalid, the script falls back to a small set of baked-in
default handles so it still runs.
How It Works
The script calls https://api.x.ai/v1/responses with the x_search tool enabled. Grok
searches X in real-time and returns a summarized digest. The scanner adds reliability on top:
What ships with it
5 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.
- 9d ago First seen · 127 lines · 99 tokens per session scan A 772f8f72cb70
x-scanner is a skill published in the GitHub repository reymerekar7/rm-skills (37 stars, last pushed 1mo ago), licensed MIT. It adds 99 tokens to every session and 1,274 once invoked, about $0.0005 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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