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 SELAT-AI/selat-openclaw-skills --skill twitter-researchgit clone --depth 1 https://github.com/SELAT-AI/selat-openclaw-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/selat-ai/selat-openclaw-skills/twitter-research)<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.
<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>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 | $0.00145 | $0.01657 |
| Opus 5.5 | $0.00058 | $0.00663 |
| Sonnet 5.5 | $0.00029 | $0.00331 |
| Haiku 4.5 | $0.00015 | $0.00166 |
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 1mo 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 — 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/runis 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 runexecutes 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.
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.
- 1mo ago First seen · 146 lines · 145 tokens per session scan A bb1b0c8b5aad
twitter-research is a skill published in the GitHub repository SELAT-AI/selat-openclaw-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 145 tokens to every session and 1,657 once invoked, about $0.0006 per session on Opus 5.5. 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.
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