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 runxhq/runx --skill twittergit clone --depth 1 https://github.com/runxhq/runxWrote 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/runxhq/runx/twitter)<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.
<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>- 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 | $0.00053 | $0.03776 |
| Opus 5 | $0.00026 | $0.01888 |
| Sonnet 5 | $0.00011 | $0.00755 |
| Haiku 4.5 | $0.00005 | $0.00378 |
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.
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 — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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_eventdata-store#read_events
What this skill does
Five runners:
read: collect account evidence from the live API. Queries:snapshot,posts,mentions,search,following,followers. Emitstwitter.evidence.v1. Read-only; no gate.read-archive: inspect one contained X archive export (tweets.js,following.js, orfollower.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 sametwitter.evidence.v1packet; no gate.plan: turn one bounded objective plus evidence intotwitter.plan.v1, an explicit list of typed acts with rationale, using agent judgment, then bind the exact plan through nativedata.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 exposestwitter_plan.dataand the matchingdigest_result.data.digestrequired byexecute; 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:postspagestweets.jsand emitsdelete_postacts (predicate: author, date range, engagement threshold), with identical results across page sizes;usersreads a boundedfollowing.jsbundle and emitsunfollowacts (predicate:non_mutual: truefor accounts you follow that do not follow back, needingfollower.jstoo, or an explicituser_idslist). Emitstwitter.selection.v1carrying a digest-boundtwitter_plan.execute: run an approved plan through the X API behind an approval gate, act by act, sealing per-act provider evidence intotwitter.execution.v1and 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.
What ships with it
19 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.
- fixtures/data/archive-follower.js 132 B runs code
- fixtures/data/archive-following.js 338 B runs code
- fixtures/data/archive-tweets.js 1.4 KB runs code
- fixtures/default-requires-twitter-binding.yaml 1.2 KB
- fixtures/execute-digest-mismatch-refuses.yaml 1.3 KB
- fixtures/execute-refused-plan-noop.yaml 1.4 KB
- fixtures/execute-stale-progress-refuses.yaml 1.7 KB
- fixtures/plan-missing-evidence-needs-input.yaml 1.0 KB
- fixtures/plan-prune-ready.yaml 2.1 KB
- fixtures/read-archive-audit.yaml 1.3 KB
- fixtures/select-nonmutual-ready.yaml 929 B
- fixtures/select-retweets-ready.yaml 871 B
- twitter-execution-requests.mjs 5.9 KB runs code
- twitter-execution-result.mjs 8.5 KB runs code
- twitter-execution-values.mjs 1.2 KB runs code
- twitter-execution.mjs 7.4 KB runs code
- twitter-read.mjs 12 KB runs code
- twitter-selection.mjs 11 KB runs code
- X.yaml 39 KB
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.
- 8d ago First seen · 297 lines · 53 tokens per session scan A d97463a3e7f6
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.
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