twitter

twitter is a skill for Claude Code, Codex from runxhq/runx. It costs 53 tokens per session (3,776 once invoked), scanned A, original, Apache-2.0.

A governed workflow for managing an X (formerly Twitter) account through evidence gathering, action planning, approval, and execution.

In plain words
What is it for?
It helps inspect posts, mentions, followers, and other account data, then plan and carry out approved publishing or account-maintenance actions.
Why use it?
It prevents posts or account changes from reaching the public account without explicit approval and a record of what happened.

Skill for Claude CodeCodex

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

Good fit It helps inspect posts, mentions, followers, and other account data, then plan and carry out approved publishing or account-maintenance actions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/runxhq/runx/twitter
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 runxhq/runx --skill twitter
Clone the repo
git clone --depth 1 https://github.com/runxhq/runx

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

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/runxhq/runx/twitter"><img src="https://agentmods.dev/badge/skills/runxhq/runx/twitter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,776 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 pass 7 Sept 2026
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 $0.00053 $0.03776
Opus 5 $0.00026 $0.01888
Sonnet 5 $0.00011 $0.00755
Haiku 4.5 $0.00005 $0.00378

Measured 8d ago against content hash d97463a3e7f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

twitter 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 8d ago.

The scan reads SKILL.md. This mod also ships 9 executable files (fixtures/data/archive-follower.js, fixtures/data/archive-following.js, fixtures/data/archive-tweets.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.

skills/twitter/SKILL.md · 297 lines

How it starts

The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Twitter

One account, three lanes: read evidence, plan typed acts, execute an approved plan.

This is the public branded X (Twitter) catalog skill for the send-as action family. Its core invariant: the agent may read, audit, draft, and plan freely, but every act that publishes to a public timeline or mutates the account stops at a human approval gate, and the sealed receipt proves which acts ran, against which plan digest, with which provider evidence.

Write for the operator who owns the account, the reviewer who approves a live act, and downstream skills that consume the resulting packets. Keep each plan to the smallest evidence-backed act set that satisfies the objective. Existing post and user ids must come from supplied evidence, never memory or guesswork; name missing evidence as a blocker.

Composes

  • data-store#append_event
  • data-store#read_events

What this skill does

Five runners:

  • read: collect account evidence from the live API. Queries: snapshot, posts, mentions, search, following, followers. Emits twitter.evidence.v1. Read-only; no gate.
  • read-archive: inspect one contained X archive export (tweets.js, following.js, or follower.js) through the runtime's digest-bound artifact page seam. Twitter code receives bounded, record-complete pages and never a path or whole-file escape hatch. The runtime snapshots up to 512 MiB and this skill requests 512 KiB pages; the page size is not a total archive limit. Emits the same twitter.evidence.v1 packet; no gate.
  • plan: turn one bounded objective plus evidence into twitter.plan.v1, an explicit list of typed acts with rationale, using agent judgment, then bind the exact plan through native data.digest. This is the curated lane, for dozens of acts that each deserve a reason. A plan is a draft; it delivers nothing. The result exposes twitter_plan.data and the matching digest_result.data.digest required by execute; callers never calculate the digest themselves.
  • select: the bulk lane. Apply a deterministic predicate to an archive export and emit a compact plan, no agent judgment. Use it when the criterion is mechanical and the match set runs to thousands, where a per-item rationale would be wrong and would exceed the runtime output limit. Two targets: posts pages tweets.js and emits delete_post acts (predicate: author, date range, engagement threshold), with identical results across page sizes; users reads a bounded following.js bundle and emits unfollow acts (predicate: non_mutual: true for accounts you follow that do not follow back, needing follower.js too, or an explicit user_ids list). Emits twitter.selection.v1 carrying a digest-bound twitter_plan.
  • execute: run an approved plan through the X API behind an approval gate, act by act, sealing per-act provider evidence into twitter.execution.v1 and appending one compact progress fact to a durable execution ledger. A batch is always a contiguous plan prefix and native HTTP stops at the first failed or rate-limited request, so a monotonic cursor—not an accumulated id list—is enough to resume safely.

Read the full file on GitHub · 297 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. 8d ago First seen · 297 lines · 53 tokens per session scan A d97463a3e7f6

Subscribe to this mod's changes

twitter is a skill published in the GitHub repository runxhq/runx (87 stars, last pushed 3d ago), licensed Apache-2.0. It adds 53 tokens to every session and 3,776 once invoked, about $0.0003 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 2026-09-03.