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 TommyBez/evex --skill typefully-best-practicesgit clone --depth 1 https://github.com/TommyBez/evexWrote 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/tommybez/evex/typefully-best-practices)<a href="https://agentmods.dev/skills/tommybez/evex/typefully-best-practices"><img src="https://agentmods.dev/badge/skills/tommybez/evex/typefully-best-practices/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/tommybez/evex/typefully-best-practices"><img src="https://agentmods.dev/badge/skills/tommybez/evex/typefully-best-practices.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00027 | $0.01006 |
| Opus 5 | $0.00014 | $0.00503 |
| Sonnet 5 | $0.00005 | $0.00201 |
| Haiku 4.5 | $0.00003 | $0.00101 |
Grade A, and why
typefully-best-practices 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 9d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Guidance for drafting X posts and creating Typefully drafts without violating X's automation rules or producing duplicate drafts. Apply these rules whenever an X draft is being authored or created through Typefully.
X automation compliance
X's automation rules apply to anything posted through the Typefully API on behalf of an account. The agent only creates drafts; it never publishes or schedules them, but the same rules govern the content that lands in the queue.
- No duplicate content across drafts in the same run. Each of the three draft candidates must take a distinct angle on the same hot topic. Reusing the same text across drafts risks an X duplicate-content flag.
- No unsolicited automated replies. Never set a reply target on a draft unless the user explicitly asked for a reply to a specific post. The agent creates top-level posts only.
- No trending manipulation. Do not stuff hashtags or pile onto a trending topic to game visibility. The drafts react to a real signal from watched profiles, not to the trending tab.
- No fake engagement. The agent does not like, repost, follow, or reply. It only creates drafts.
- Label AI-drafted posts. X requires a "made with AI" label on LLM-generated
posts.
X_HOT_TOPIC_DRAFT_MADE_WITH_AIdefaults totrueandcreate_x_draftssetsmade_with_ai: trueon every X post. Only disable the label if a human rewrites the posts before publishing. - Respect rate limits. The Typefully API rate-limits draft creation per user and per social set. One run produces at most three drafts; do not loop create calls to retry a failed draft in the same step.
See x-automation for the full compliance model.
Exactly-once draft creation
The Typefully v2 API does not accept a server-side idempotency key, so a replayed
Eve step would normally create a second draft. The agent defends against that
with a per-draft idempotencyKey plus an in-process cache of successful
creates:
What ships with it
2 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.
- 9d ago First seen · 82 lines · 27 tokens per session scan A 6a28f90434c3
typefully-best-practices is a skill published in the GitHub repository TommyBez/evex (24 stars, last pushed today), licensed MIT. It adds 27 tokens to every session and 1,006 once invoked, about $0.0001 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 2026-08-30.
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