fact-check-x-unified

fact-check-x-unified is a skill for Claude Code, Codex from ASI2030/Fact-Check-X. It costs 70 tokens per session (2,370 once invoked), scanned A, original, Apache-2.0.

A workflow for checking claims against reference answers and authoritative sources across multiple platforms. Fact-checking means testing whether statements are accurate and supported by evidence.

In plain words
What is it for?
It captures platform answers and citations, compares them with local knowledge points, runs authoritative checks, records stage confirmations, and creates HTML reports.
Why use it?
It organizes collection, comparison, verification, checkpoints, and reports so claims are not judged from one answer alone.

Skill for Claude CodeCodex

Written for Claude Code and Codex: shipped in a Claude Code plugin, but also agents/openai.yaml present. Also seen: mentions Claude Code; mentions Codex.

Part of the fact-check-x plugin — 5 skills shipped together

Good fit It captures platform answers and citations, compares them with local knowledge points, runs authoritative checks, records stage confirmations, and creates HTML reports.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/asi2030/fact-check-x/fact-check-x-unified
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 ASI2030/Fact-Check-X --skill fact-check-x-unified
Clone the repo
git clone --depth 1 https://github.com/ASI2030/Fact-Check-X

Made for: Claude Code, Codex.

Or install fact-check-x, the plugin that ships this one along with the rest of its 5 skills.

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 fact-check-x-unified

README.md
[![agentmods](https://agentmods.dev/badge/skills/asi2030/fact-check-x/fact-check-x-unified/github.svg)](https://agentmods.dev/skills/asi2030/fact-check-x/fact-check-x-unified)
Your own site
<a href="https://agentmods.dev/skills/asi2030/fact-check-x/fact-check-x-unified"><img src="https://agentmods.dev/badge/skills/asi2030/fact-check-x/fact-check-x-unified/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.

agentmods 80×15 button for fact-check-x-unified

Your own site · 80×15
<a href="https://agentmods.dev/skills/asi2030/fact-check-x/fact-check-x-unified"><img src="https://agentmods.dev/badge/skills/asi2030/fact-check-x/fact-check-x-unified.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,370 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 $0.00070 $0.02370
Opus 5 $0.00035 $0.01185
Sonnet 5 $0.00014 $0.00474
Haiku 4.5 $0.00007 $0.00237

Measured 8d ago against content hash 3abf1de82570, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

fact-check-x-unified 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.

The scan reads SKILL.md. This mod also ships 7 executable files (scripts/common.py, scripts/fact_check_x.py, scripts/trusted_search_config.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/fact-check-x-unified/SKILL.md · 154 lines

How it starts

The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Fact-Check-X 统一入口

本技能只做编排,不内嵌三个业务层。它按以下顺序调用兄弟技能:

  1. llm-answer-reference-compare:多平台回答、引用与现场存证采集。
  2. fact-check-x-knowledge-compare:本地知识点结构化对比,可选。
  3. fact-check-x-authoritative-verify:逐知识点并发权威核验与平台表现报告。

所有语义拆解和证据裁决由当前承载技能的智能体完成。脚本不调用任何模型 API。

依赖定位

四个技能放在同一目录时可直接运行。也可设置:

export FACTCHECK_SKILLS_DIR="<四个技能的父目录>"

检查依赖:

python3 scripts/fact_check_x.py locate

完整流程

先采集 results.json,然后准备知识点对比:

python3 scripts/fact_check_x.py prepare-comparison \
  --results <results.json> \
  --run-dir <run>

命令会同步生成“各方答案汇总”,在运行目录顶层生成 01-capture-report.html,并通过 deliverables 返回用户可见路径。调用方必须先用该路径发送真正的 Markdown 文件链接,再继续知识点对比;禁止只显示反引号路径。

默认交互模式下,程序会把阶段状态写入 stage-checkpoints.json。调用方发送本阶段产物并收到用户“继续下一步”后,必须使用 checkpoint.acknowledgement.token 执行:

python3 scripts/fact_check_x.py acknowledge-stage \
  --run-dir <run> --stage <checkpoint.stage> \
  --token <checkpoint.acknowledgement.token> --decision continue

未确认时,下一阶段命令会直接失败。即使用户最初要求完整连续执行,也必须依次展示每个阶段产物并取得确认;不存在可绕过确认的自动推进模式。

当前智能体读取 <run>/comparison-task.json,写入 <run>/comparison-analysis.json,再执行:

拆解时,原子性同时约束知识点和各平台 claim。一个原句包含多个独立义务、条件、对象、数值或后果时必须拆点,每个 claim 只保留当前事实;平台独有的实质新增事实也要另起无锚点知识点,不能并入宽泛知识点后复用深知晓锚点免查。

python3 scripts/fact_check_x.py complete-comparison \
  --results <results.json> \
  --run-dir <run>

命令会在运行目录顶层生成 02-comparison-report.html,并通过 deliverables 返回路径;调用方必须把它作为独立可点击文件展示给用户。报告必须包含明确标为“未核验”的综合草案。默认交互模式下,用户确认继续后才能进入权威核验。

生成每个知识点的独立云端请求并并发取证:

python3 scripts/fact_check_x.py prepare-authority --run-dir <run>
python3 scripts/fact_check_x.py search-authority --run-dir <run> --max-workers 12

知识点已有深知晓/深知晓(深度溯源)本次回答所附的官方材料,或其他平台本次回答所附的 gov.cn 材料,且原文确实支持当前主张时,直接复用为官方证据,不调用可信搜索。只有不属于上述情形或已有材料不足以裁决时,才是非免查知识点。

若存在非免查知识点但本机尚无可信搜索配置,prepare-authoritysearch-authority 会返回 status=configuration_requireduserPromptconfiguration.command 并以非零状态退出。调用方先展示登录提示,再前台执行该命令。用户只需在自动打开的深知 MaaS 页面完成登录;组件会自动复用已有完整 Key,没有时创建 Fact-Check-X 专用 Key,验证后保存到 ~/.fact-check-x/credentials/trusted-search-key。Codex、Claude Code、WorkBuddy 等载体共享该配置,检测到已有 Key 时直接跳过登录。配置成功后调用方自动重跑 prepare-authority,不得要求用户复制 Key、编辑 shell 配置、回复“已配置”,也不得改用深知晓来源或普通搜索绕过。

Read the full file on GitHub · 154 lines

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. 8d ago Changed 3abf1de82570
  2. 12d ago First seen · 154 lines · 70 tokens per session scan A e02b907cfb35

Subscribe to this mod's changes

fact-check-x-unified is a skill published in the GitHub repository ASI2030/Fact-Check-X (1 stars, last pushed yesterday), licensed Apache-2.0. It adds 70 tokens to every session and 2,370 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 2026-08-31.