write-tweet

write-tweet is a skill for Claude Code, Codex from aeonfun/aeon. It costs 41 tokens per session (9,510 once invoked), scanned C, original, MIT.

A social-post drafting tool for creating standalone posts, multi-post threads, remixes of earlier posts, and revisions of saved drafts.

In plain words
What is it for?
Use it to draft new posts, turn an idea into a thread, rewrite earlier posts, or revise the latest draft.
Why use it?
It removes the need to format each kind of post manually and helps keep recent topics and past drafts in context.

Skill for Claude CodeCodex

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

Good fit Use it to draft new posts, turn an idea into a thread, rewrite earlier posts, or revise the latest draft.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aeonfun/aeon/write-tweet
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 aeonfun/aeon --skill write-tweet
Clone the repo
git clone --depth 1 https://github.com/aeonfun/aeon

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 write-tweet

README.md
[![agentmods](https://agentmods.dev/badge/skills/aeonfun/aeon/write-tweet.svg)](https://agentmods.dev/skills/aeonfun/aeon/write-tweet)
Your own site
<a href="https://agentmods.dev/skills/aeonfun/aeon/write-tweet"><img src="https://agentmods.dev/badge/skills/aeonfun/aeon/write-tweet.svg" alt="Measured on agentmods" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 9,510 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 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: 9 findings, 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 Prompt Injection · line 380
    Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.
    Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
  • medium Data Exfiltration · line 83
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 83
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 434
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 446
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 627
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 635
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 434
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
  • medium Data Exfiltration · line 631
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 $0.00041 $0.09510
Opus 5 $0.00020 $0.04755
Sonnet 5 $0.00008 $0.01902
Haiku 4.5 $0.00004 $0.00951

Measured 3d ago against content hash 308e7ee0a21d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade C, and why

write-tweet scanned grade C with 2 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 3d 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.

Hidden instructionshighPrompt injection

Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.

<!-- autoresearch: variation B — sharper output via remixability pre-filter, strategy-rotation, skip-gate for un-remixable originals, post-write self-edit; folded in A's multi-angle queries + engagement counts and C's so

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

If `XAI_API_KEY` is set, search X for what people are already saying about the topic. A direct `curl` to the X.AI Responses API is the **primary** path for this X read (see **Fetching**; set the Bash tool `timeout` ≥1800
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

skills/write-tweet/SKILL.md · 643 lines

How it starts

The opening of the file, as written. The whole thing — 643 lines — stays where its author put it; the contents beside it link to each section on GitHub.

${var}[format] [argument]. Pick one of three formats, then pass its argument. Empty ⇒ drafts (standalone tweet drafts). thread … ⇒ a multi-tweet thread. remix …remix of your past tweets. revise:<instruction>revise the last saved draft (the Telegram force-reply shape, e.g. revise:make it punchier). See Selector below.

Read memory/MEMORY.md for context on recent articles, digests, topics being tracked, and the operator's tracked handles/token. Each branch then reads its own memory/logs/ window (drafts: 3 days, thread: 7 days, remix: 14 days) — see the branch.

Selector

Revise intercept first (Telegram force-reply). If ${var} starts with revise: → jump straight to Branch: REVISE (below) and stop; do not token-parse. This is the shape scripts/telegram-route.sh sends when the operator replies to a "refine this draft?" prompt — the revise: prefix would otherwise fall through to the drafts branch.

Otherwise, parse ${var} once, before doing anything else:

  1. Trim whitespace. Take the first token (everything up to the first space or the first :), lowercased.
  2. If that token is one of drafts, thread, remix → that's the format. The argument is the remainder of ${var} after stripping the keyword and one optional following : and surrounding whitespace.
  3. Otherwise → format is drafts and the argument is the entire ${var} (backward-compatible with the legacy var = topic/URL behaviour).
${var} Format Argument Behaviour
`` (empty) drafts Auto-select the most tweetable insight from today's logs
prediction markets are broken drafts prediction markets are broken Drafts on that topic
https://arxiv.org/abs/2401.00001 drafts that URL Drafts about the linked source
drafts: thread models are underrated drafts thread models are underrated Escape hatch: force drafts on a topic that starts with a reserved word
thread thread Auto-pick the day's highest-signal event and thread it
thread oracle incentives are broken thread oracle incentives are broken Thread on that topic
remix remix Remix past tweets, default 180d window
remix 1y remix 1y Remix, 1-year window
remix 2025-01-01:2025-03-01 remix 2025-01-01:2025-03-01 Remix, explicit date range

Then dispatch to the matching branch below. Only run the selected branch.


Read the full file on GitHub · 643 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. 3d ago First seen · 643 lines · 41 tokens per session scan C 308e7ee0a21d

Subscribe to this mod's changes

write-tweet is a skill published in the GitHub repository aeonfun/aeon (716 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 9,510 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it C with 2 findings (hidden instructions, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.