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 mturac/everything-openai-codex --skill crosspostgit clone --depth 1 https://github.com/mturac/everything-openai-codexWrote 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/mturac/everything-openai-codex/crosspost)<a href="https://agentmods.dev/skills/mturac/everything-openai-codex/crosspost"><img src="https://agentmods.dev/badge/skills/mturac/everything-openai-codex/crosspost/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/mturac/everything-openai-codex/crosspost"><img src="https://agentmods.dev/badge/skills/mturac/everything-openai-codex/crosspost.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 | $0.00049 | $0.00739 |
| Opus 5.5 | $0.00020 | $0.00296 |
| Sonnet 5.5 | $0.00010 | $0.00148 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
crosspost 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.
This is a copy
100% identical to crosspost — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Crosspost
Distribute content across platforms without turning it into the same fake post in four costumes.
When to Activate
- the user wants to publish the same underlying idea across multiple platforms
- a launch, update, release, or essay needs platform-specific versions
- the user says "crosspost", "post this everywhere", or "adapt this for X and LinkedIn"
Core Rules
- Do not publish identical copy across platforms.
- Preserve the author's voice across platforms.
- Adapt for constraints, not stereotypes.
- One post should still be about one thing.
- Do not invent a CTA, question, or moral if the source did not earn one.
Workflow
Step 1: Start with the Primary Version
Pick the strongest source version first:
- the original X post
- the original article
- the launch note
- the thread
- the memo or changelog
Use content-engine first if the source still needs voice shaping.
Step 2: Capture the Voice Fingerprint
Run brand-voice first if the source voice is not already captured in the current session.
Reuse the resulting VOICE PROFILE directly.
Do not build a second ad hoc voice checklist here unless the user explicitly wants a fresh override for this campaign.
Step 3: Adapt by Platform Constraint
X
- keep it compressed
- lead with the sharpest claim or artifact
- use a thread only when a single post would collapse the argument
- avoid hashtags and generic filler
- add only the context needed for people outside the niche
- do not turn it into a fake founder-reflection post
- do not add a closing question just because it is LinkedIn
- do not force a polished "professional tone" if the author is naturally sharper
Threads
- keep it readable and direct
- do not write fake hyper-casual creator copy
- do not paste the LinkedIn version and shorten it
Bluesky
- keep it concise
- preserve the author's cadence
- do not rely on hashtags or feed-gaming language
Posting Order
Default:
- post the strongest native version first
- adapt for the secondary platforms
- stagger timing only if the user wants sequencing help
What ships with it
1 file 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.
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 · 111 lines · 49 tokens per session scan A ef25ac009f34
crosspost is a skill published in the GitHub repository mturac/everything-openai-codex (86 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 739 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to crosspost, differing in 1 line, and is treated as a copy.
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