twitter-research

twitter-research is a skill for Claude Code, Codex from SELAT-AI/selat-openclaw-skills. It costs 145 tokens per session (1,657 once invoked), scanned A, original, MIT.

A read-only research guide for Twitter/X accounts, posts, replies, mentions, followers, retweeters, topic searches, and trends. It is designed for gathering information without posting or changing accounts.

In plain words
What is it for?
Use it to inspect a profile, find recent posts or mentions, examine replies and retweets, search topics, check trends, or summarize public activity around an account or subject.
Why use it?
It gives the agent a defined set of lookups and makes clear that protected accounts are unavailable and each live read is paid. This helps answer social-media research questions with the smallest needed set of searches.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to inspect a profile, find recent posts or mentions, examine replies and retweets, search topics, check trends, or summarize public activity around an account or subject.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/selat-ai/selat-openclaw-skills/twitter-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 SELAT-AI/selat-openclaw-skills --skill twitter-research
Clone the repo
git clone --depth 1 https://github.com/SELAT-AI/selat-openclaw-skills

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 twitter-research

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/selat-ai/selat-openclaw-skills/twitter-research"><img src="https://agentmods.dev/badge/skills/selat-ai/selat-openclaw-skills/twitter-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 145 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,657 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.
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 $0.00145 $0.01657
Opus 5 $0.00072 $0.00829
Sonnet 5 $0.00029 $0.00331
Haiku 4.5 $0.00015 $0.00166

Measured 12d ago against content hash bb1b0c8b5aad, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

twitter-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 12d 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.

skills/twitter-research/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

twitter-research

Research Twitter/X, keylessly and pay-per-read. This skill is a curated menu of 9 read-only endpoints on SELAT's own first-party Twitter API — account reads (profile, recent tweets, mentions, followers), tweet reads (details, replies, retweeters), topic search, and trends. You (the agent) pick the reads a request actually needs, run them, and synthesize the answer in plain language.

It wraps a SELAT skill: a declarative, vetted recipe of paid API calls (no API keys, no signups) settled in USDC as x402 via Circle Gateway. The selat CLI resolves the vetted endpoints and prints a per-step receipt. Read-only — it never posts, likes, or follows, and cannot see protected/private accounts.

Cost — read this first

  • Every read is a real paid API call in USDC from the user's own Circle Agent Wallet (MPC self-custody — SELAT never holds keys or funds).
  • Prices and spend limits live in the underlying SELAT skill, not here — the live 402 quote from selat skill verify/run is the price source of truth, so this wrapper doesn't restate dollar figures (they'd only drift).
  • It's a menu, not a pipeline. Map the request to the smallest set of reads (a profile question is 1 read, "how did this tweet land" is 3), and pass only the params those reads use. selat skill run executes every step, so pass the relevant params and treat the unused reads' output as noise — or keep runs cheap by asking a focused question.
  • Always dry-run first (Step 1 — free, no wallet), show the user the real quoted prices, and get their OK before any wallet setup or paid run.
  • Never ask for, paste, or handle a private key. Wallet auth is the CLI's Circle integration.

Step 0 — get the CLI (free, no account)

If selat isn't on PATH yet, install it — one npm package, no signup:

selat --version || npm install -g @selat-ai/selat-cli

Installing the CLI creates nothing money-related — no wallet, no account, no keys.

Read the full file on GitHub · 146 lines

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. 12d ago First seen · 146 lines · 145 tokens per session scan A bb1b0c8b5aad

Subscribe to this mod's changes

twitter-research is a skill published in the GitHub repository SELAT-AI/selat-openclaw-skills (2 stars, last pushed 29d ago), licensed MIT. It adds 145 tokens to every session and 1,657 once invoked, about $0.0007 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 2026-08-31.

Related

Other skills, from other repositories

skill-creator

Use this skill when a contributor wants to build, author, scaffold, verify, or submit a new skill to the SELAT skill hub (selat-skills) — e.g. "create a skill", "build a selat skill", "add a skill to the hub", "contribute a skill", "how do I write a manifest.json", "verify my skill", "submit my skill", "wrap an MPP…

SELAT-AI/selat-skills · 133 tokens

self-evolving-agent

Use this skill when the user wants to design or operate a budgeted economic agent with its own operational identity, AgentMail address, agent-wallet treasury, infrastructure budget, social and financial intelligence loop, monetization or trading hypotheses, and reinvestment policy. The skill enforces treasury…

SELAT-AI/selat-skills · 89 tokens

perplexity-search

Use this skill when the user wants a grounded web answer or research from Perplexity without an API key — e.g. "search the web for ", "what's the latest on ", "pull cited web context on ", "research with sources", "do a deep-research report on ". Runs Perplexity's x402 endpoints (search / sonar answer / async…

SELAT-AI/selat-skills · 120 tokens

twitter-research

Use this skill for read-only Twitter/X research on the SELAT-native Twitter API (catalog.selat.ai) — profiles, recent tweets, mentions, followers, tweet details/replies/retweeters, topic search, and trends. Triggers on "who is @X on Twitter", "recent tweets from X", "who's mentioning X", "how did this tweet do / who…

SELAT-AI/selat-skills · 167 tokens

selat-discovery

Use the moment you're about to tell the user you can't do something — or about to suggest they sign up for, get an API key for, or go to an external tool, site, or API to do it themselves. Covers what's beyond a model natively: image/video/audio/voice generation, translation, transcription, web search/scraping…

SELAT-AI/selat-plugins · 203 tokens

enrich-waterfall

Use this skill when the user wants to enrich a person or company from a partial identifier — e.g. "enrich this email", "find the work email and phone for X at Y", "who is this person", "build a lead profile for stripe.com", "company enrichment for this domain", "find their LinkedIn / Twitter", "get me funding and…

SELAT-AI/selat-skills · 193 tokens