AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
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 sickn33/agentic-awesome-skills --skill adhxgit clone --depth 1 https://github.com/sickn33/agentic-awesome-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/sickn33/agentic-awesome-skills/adhx)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/adhx"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/adhx/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/sickn33/agentic-awesome-skills/adhx"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/adhx.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
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 →
- medium Agent Snooping · line 87 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Prompt Injection · line 121 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
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 | $0.00049 | $0.01109 |
| Opus 5 | $0.00024 | $0.00554 |
| Sonnet 5 | $0.00010 | $0.00222 |
| Haiku 4.5 | $0.00005 | $0.00111 |
Grade A, and why
adhx scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
2. **Fetch the JSON** using curl: Copies of this mod
8 near-identical copies found in the catalogue:
How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADHX - X/Twitter Post Reader
Fetch any X/Twitter post as structured JSON for analysis using the ADHX API.
Overview
ADHX provides a free API that returns clean JSON for any X post, including full long-form article content. This is far superior to scraping or browser-based approaches for LLM consumption. Works with regular tweets and full X Articles.
When to Use This Skill
- Use when a user shares an X/Twitter link and wants to read, analyze, or summarize the post
- Use when you need structured data from an X/Twitter post (author, engagement, content)
- Use when working with long-form X Articles that need full content extraction
API Endpoint
https://adhx.com/api/share/tweet/{username}/{statusId}
URL Patterns
Extract username and statusId from any of these URL formats:
| Format | Example |
|---|---|
x.com/{user}/status/{id} |
https://x.com/dgt10011/status/2020167690560647464 |
twitter.com/{user}/status/{id} |
https://twitter.com/dgt10011/status/2020167690560647464 |
adhx.com/{user}/status/{id} |
https://adhx.com/dgt10011/status/2020167690560647464 |
Workflow
When a user shares an X/Twitter link:
- Parse the URL to extract
usernameandstatusIdfrom the path segments - Fetch the JSON using curl:
curl -s "https://adhx.com/api/share/tweet/{username}/{statusId}"
- Use the structured response to answer the user's question (summarize, analyze, extract key points, etc.)
Response Schema
{
"id": "statusId",
"url": "original x.com URL",
"text": "short-form tweet text (empty if article post)",
"author": {
"name": "Display Name",
"username": "handle",
"avatarUrl": "profile image URL"
},
"createdAt": "timestamp",
"engagement": {
"replies": 0,
"retweets": 0,
"likes": 0,
"views": 0
},
"article": {
"title": "Article title (for long-form posts)",
"previewText": "First ~200 chars",
"coverImageUrl": "hero image URL",
"content": "Full markdown content with images"
}
}
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 · 133 lines · 49 tokens per session scan A 0ad8b3210efe
adhx is a skill published in the GitHub repository sickn33/agentic-awesome-skills (46,230 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 1,109 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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