gingiris-twitter-agent-ops

gingiris-twitter-agent-ops is a skill for Claude Code from Gingiris-1031/gingiris-skills. It costs 360 tokens per session (7,389 once invoked), scanned A, original, MIT.

An operating guide for managing two Twitter/X accounts, based on described posting, monitoring, analytics, and content-checking practices. It includes procedures for detecting failures and inaccurate or repetitive posts.

In plain words
What is it for?
Collecting account details, maintaining a content library and operations log, checking data sources, scheduling posts, and reviewing account performance and incidents.
Why use it?
It addresses missed scheduled posts, unreliable metrics, and overuse of the same topic by adding checks, records, and limits.

Skill for Claude Code

Written for Claude Code: when-to-use in frontmatter.

Good fit Collecting account details, maintaining a content library and operations log, checking data…

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Install with agentmods
npx agentmods add skills/gingiris-1031/gingiris-skills/gingiris-twitter-agent-ops
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 Gingiris-1031/gingiris-skills --skill gingiris-twitter-agent-ops
Clone the repo
git clone --depth 1 https://github.com/Gingiris-1031/gingiris-skills

Made for: Claude Code.

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 gingiris-twitter-agent-ops

README.md
[![agentmods](https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gingiris-twitter-agent-ops.svg)](https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-twitter-agent-ops)
Your own site
<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-twitter-agent-ops"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gingiris-twitter-agent-ops.svg" alt="Measured on agentmods" height="20"></a>
Per session 360 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,389 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00360 $0.07389
Opus 5 $0.00180 $0.03694
Sonnet 5 $0.00072 $0.01478
Haiku 4.5 $0.00036 $0.00739

Measured 7d ago against content hash 001fe3720eca, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

gingiris-twitter-agent-ops 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 7d 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.

skills/gingiris-twitter-agent-ops/SKILL.md · 708 lines

How it starts

The opening of the file, as written. The whole thing — 708 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Twitter/X Agent 运营 SOP v2

版本说明:v2 草稿。v1 给了你整套方法论框架,v2 的重点是: 「已经在跑了,怎么确保不出事、出了事怎么发现、发现了怎么处理」。


⚠️ 开始之前:三个真实事故

在讲 SOP 之前,先讲三个真实踩过的坑。这三件事决定了 v2 的核心设计。

事故 1:cron 超时失败 2 周没人发现

cron job 连续超时失败,没有任何监控机制,整整 2 周没有推文发出。等发现时,粉丝增长已经明显停滞,算法分发也已经冷却。 → v2 修复:强制日报机制,发推后必填,缺了就是异常信号。

事故 2:v0.dev 流量数据相差 17 倍,被用户公开指出

推文中引用了单一数据源(DataForSEO)的「非品牌有机搜索」数字,没有交叉验证,被 @gefei55(哥飞)等用户公开指出数据不准,差了整整 17 倍。 → v2 修复:红线自检中加入「数字来源可查」强制检查项,无来源数字不发。

事故 3:某一话题提及频率过高,被用户指出「天天蹭流量」

某段时期内容过度集中在同一品牌/话题上,用户公开反馈感觉是在持续蹭热度,而不是真正分享。 → v2 修复:任何借势话题每月提及上限 1-2 次,在发推前检查本月该话题已出现次数。


第一步:开局 Context 收集(对话式,必须完成)

Agent 开始运营前,逐步引导用户提供信息,一次只问一个问题。不要一次抛出大表格——用户看到 6 个问题就会不想填。

收集完后给出一段状态判断,再开始工作。


对话引导脚本(按顺序执行)

Q1(先问这个)

你的 Twitter/X 账号是什么?现在有多少粉丝?

→ 记录账号名和粉丝基线,作为后续增长对比


Q2

这个账号主要发什么语言?怎么发推的?

语言(可多选): A) 中文 B) 英文 C) 中英都有

发布方式: A) 手动发 B) Buffer 排期 C) API 直发(cron 自动) D) 不确定 → 先检查发布机制再继续,cron 挂掉 2 周没人知道是真实事故

→ API 直发:中文账号用 OAuth1 四字段凭证;英文账号用 Buffer channel;两套不能混用


Q3

有素材库吗?

A) 有,大概还有 ___ 条没用(存在:本地文件 / Notion / 飞书 / 其他) B) 有,但不确定有多少 C) 没有

→ A 且条数 ≤ 3:本次先补素材,再排期 → C:第一任务建素材库,今天不开始写推文


Q4

最近发推有记录吗?

A) 有 MASTER-STATUS.md 或类似运营日志 B) 有,我可以粘贴最近几条推文 C) 没有任何记录

→ A 或 B:检查是否有断更,避免重复内容 → C:先建 MASTER-STATUS.md,这是整个系统的单一真相来源


Q5

你现在最想让读者记住你的哪 1-2 件事?受众是什么人?

(自由填写,没有选项——这个要你自己说)

→ 确定内容方向,避免选题漂移


Q6(最后问)

现在最重要的目标是什么?

A) 涨粉 B) 引流到某个链接(是哪个链接?___) C) 建立信任感 / 个人品牌 D) 以上都有,但最重要的是 ___

→ CTA 链接写进每条推文的 reply 策略,不放正文(正文带链接算法惩罚展示量 30-90%)


全部收集后:输出状态判断

📊 当前状态:
- 账号:[@handle],当前 [X] 粉
- 发布机制:[OAuth1 直发 / Buffer / 手动]
- 素材库:[N] 条可用
- 上周发布:[有记录 / 无记录,需建 MASTER-STATUS.md]
- 内容方向:[用户给的 1-2 件事]
- 本阶段 CTA:[目标 + 链接]

→ 接下来做什么:[3 步以内]

判断矩阵(Agent 内部参考)

情况 判断 处理方式
cron 状态不确定 🚨 紧急 先检查 cron,确认正常再开始内容工作
素材库 ≤ 3 条 ⚠️ 预警 本次运营优先补充素材库,不排期
素材库为空 🚨 阻塞 必须先建素材库才能排期
上周发布记录缺失 ⚠️ 提醒 让用户打开 MASTER-STATUS.md 核查
MASTER-STATUS.md 不存在 🚨 首次运营 本次任务先建立 MASTER-STATUS.md

Read the full file on GitHub · 708 lines

Files

What ships with it

6 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.

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. 7d ago First seen · 708 lines · 360 tokens per session scan A 001fe3720eca

Subscribe to this mod's changes

gingiris-twitter-agent-ops is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (77 stars, last pushed 2d ago), licensed MIT. It adds 360 tokens to every session and 7,389 once invoked, about $0.0018 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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