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 2233admin/design-pipeline --skill write-like-meng-on-xgit clone --depth 1 https://github.com/2233admin/design-pipelineWrote 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/2233admin/design-pipeline/write-like-meng-on-x)<a href="https://agentmods.dev/skills/2233admin/design-pipeline/write-like-meng-on-x"><img src="https://agentmods.dev/badge/skills/2233admin/design-pipeline/write-like-meng-on-x/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/2233admin/design-pipeline/write-like-meng-on-x"><img src="https://agentmods.dev/badge/skills/2233admin/design-pipeline/write-like-meng-on-x.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 | $0.00111 | $0.01665 |
| Opus 5 | $0.00056 | $0.00833 |
| Sonnet 5 | $0.00022 | $0.00333 |
| Haiku 4.5 | $0.00011 | $0.00167 |
Grade A, and why
write-like-meng-on-x 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 6d 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 write-like-meng-on-x — 0 lines 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write Like Meng on X
Start
Work from the user's Content repo unless the user names another checkout. If no Content repo is active, locate it from the available workspace roots or ask for the target before writing files.
- Read
AGENTS.mdand rungit status --short --branchbefore changing files. - Read references/voice-profile.md before drafting.
- Read only the relevant rows in references/content-source-map.md for factual and personal context.
- Search references/tweet-corpus.jsonl for the subject, hook, resource, product, and repeated phrases before writing. Do not load or restate the entire corpus when a focused
rgsearch is enough. - Treat authored X posts as voice evidence, not as copy to splice together.
Use this evidence order:
- Current user instructions and raw wording
- Recent authored posts of the same format
- Trusted personal, product, and resource context in the Content repo
- Older authored posts
- Prior generated drafts, only for continuity
Draft
Identify the format first: reply, original post, quote post, resource share, thread, or product post. Match examples from the same format because Meng's replies are looser than his standalone posts.
Keep the user's strongest original line when it already sounds natural. Improve clarity, sequence, and specificity without replacing the thought with a generic copywriting framework.
Ground the post in something real when useful:
- a product Meng has built or actively uses
- a workflow, constraint, failure, proof point, or result recorded in Content
- a resource Meng has actually shared
- a personal detail already supported by the corpus or trusted project context
Never invent usage, metrics, customers, team behavior, travel, family details, product capabilities, or results. Do not turn a resource share into a hidden product pitch.
For every rewrite or drafting request, return exactly five finished options unless the user explicitly requests another count. Put the strongest option first. Make the five options materially different in angle, structure, rhythm, or intent instead of producing five surface-level paraphrases.
What ships with it
5 files 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.
- 6d ago First seen · 134 lines · 111 tokens per session scan A 5675889197eb
write-like-meng-on-x is a skill published in the GitHub repository 2233admin/design-pipeline (9 stars, last pushed 7d ago), licensed MIT. It adds 111 tokens to every session and 1,665 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to write-like-meng-on-x, differing in 0 lines, and is treated as a copy.
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