X Research

X Research is a skill for Claude Code, Codex from notforyou23/home23. It costs 36 tokens per session (1,226 once invoked), scanned A, original, MIT.

A read-only research tool for X, the social network formerly called Twitter. It searches recent posts, reads profiles and threads, and monitors selected accounts.

In plain words
What is it for?
Researching what people say about products, launches, companies, APIs, libraries, or cultural events. It can also follow tweet conversations and prepare outreach candidates.
Why use it?
It helps you find current opinions and expert views without manually searching many conversations. It does not post or reply.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Researching what people say about products, launches, companies, APIs, libraries, or cultural events. It can also follow tweet conversations and prepare outreach candidates.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/notforyou23/home23/x-research
Install

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.

Any agent
npx skills add notforyou23/home23 --skill x-research
Clone the repo
git clone --depth 1 https://github.com/notforyou23/home23

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for X Research

README.md
[![agentmods](https://agentmods.dev/badge/skills/notforyou23/home23/x-research/github.svg)](https://agentmods.dev/skills/notforyou23/home23/x-research)
Your own site
<a href="https://agentmods.dev/skills/notforyou23/home23/x-research"><img src="https://agentmods.dev/badge/skills/notforyou23/home23/x-research/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.

agentmods 80×15 button for X Research

Your own site · 80×15
<a href="https://agentmods.dev/skills/notforyou23/home23/x-research"><img src="https://agentmods.dev/badge/skills/notforyou23/home23/x-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,226 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, 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 122
    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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00036 $0.01226
Opus 5 $0.00018 $0.00613
Sonnet 5 $0.00007 $0.00245
Haiku 4.5 $0.00004 $0.00123

Measured 10d ago against content hash 92aaacec8447, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

X Research 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 10d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (index.js), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

workspace/skills/x-research/SKILL.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

X Research

Use this skill for read-only X/Twitter research. It is separate from x: use x for direct account operations like posting, replying, or checking the authenticated timeline.

For outreach workflows, this skill should find and qualify reply targets; it should not post. Produce a queue with candidate URL, why it fits, draft reply in the user's voice, include-link yes/no, priority, and posted/skipped/failed state. Then hand selected writes to the x skill.

For X API details and query/operator notes, read references/x-api.md only if needed.

When to use

Use x-research for:

  • "what are people saying" questions
  • live discourse around launches, products, APIs, libraries, companies, or cultural moments
  • following a thread from a tweet URL into the full conversation
  • checking recent posts from a specific account
  • monitoring a short watchlist of relevant accounts

Actions

search

Search recent X posts with query shaping, recency filters, and optional markdown/json artifacts.

Input:

{
  "query": "home23 OR agent runtime",
  "quick": true,
  "sort": "likes",
  "limit": 10,
  "saveMarkdown": true
}

thread

Fetch the conversation around a tweet URL or tweet ID.

Input:

{
  "url": "https://x.com/user/status/123",
  "pages": 2
}

profile

Read recent posts from one account.

Input:

{
  "username": "frankdegods",
  "count": 10
}

tweet

Read one tweet by URL or ID.

watchlist_show / watchlist_add / watchlist_remove / watchlist_check

Manage and inspect the local X research watchlist.

cache_clear

Clear cached X research results.

Workflow

  1. Break the question into 1-3 targeted queries, not one vague broad query.
  2. Start with quick or one page unless there is a clear reason to go deeper.
  3. Follow high-signal tweets with thread or profile.
  4. Save markdown when the result should feed a synthesis or handoff.
  5. Pair with source-validation before promoting social chatter into factual claims.

Read the full file on GitHub · 157 lines

Files

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.

Changes

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.

  1. 10d ago First seen · 157 lines · 36 tokens per session scan A 92aaacec8447

Subscribe to this mod's changes

X Research is a skill published in the GitHub repository notforyou23/home23 (11 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 1,226 once invoked, about $0.0002 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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