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 ASI2030/Fact-Check-X --skill fact-check-x-knowledge-comparegit clone --depth 1 https://github.com/ASI2030/Fact-Check-XWrote 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/asi2030/fact-check-x/fact-check-x-knowledge-compare)<a href="https://agentmods.dev/skills/asi2030/fact-check-x/fact-check-x-knowledge-compare"><img src="https://agentmods.dev/badge/skills/asi2030/fact-check-x/fact-check-x-knowledge-compare/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/asi2030/fact-check-x/fact-check-x-knowledge-compare"><img src="https://agentmods.dev/badge/skills/asi2030/fact-check-x/fact-check-x-knowledge-compare.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 | $0.00079 | $0.01180 |
| Opus 5.5 | $0.00032 | $0.00472 |
| Sonnet 5.5 | $0.00016 | $0.00236 |
| Haiku 4.5 | $0.00008 | $0.00118 |
Grade A, and why
fact-check-x-knowledge-compare 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 1mo 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
知识点结构化对比
本技能是独立、可选的本地中间层。它回答“各家说了什么、哪里相同或不同、各自有没有依据、是否忠实于自己的依据”,不回答外部世界中谁最终正确。
当前承载技能的智能体(Codex、Claude Code 等)直接完成知识点拆解和语义判断。脚本只生成任务包、校验证据约束、标准化结构并渲染报告,不调用模型 API。
第一步:生成分析任务包
python3 scripts/knowledge_compare.py \
--input <run>/results.json \
--task-output <run>/comparison-task.json
阅读 comparison-task.json 后,由当前智能体写出 comparison-analysis.json。必须遵守:
-
comparison-task.json是自包含的紧凑工作集。阶段确认后严格按“读取任务包一次、写入分析一次、执行验收一次”完成,最多三次工具调用;不得读取技能源码、契约或完整results.json探路,也不得先打印或转储完整任务包。 -
任务包中的
capturedText是从完整来源正文中选出的有界原文预览,便于一次完成来源判断;完整正文仍保存在results.json,由程序在验收时校验并重建证据,智能体不得为取得全文额外展开任务。 -
合并所有成功平台中可独立核验的事实,每个知识点只表达一个事实变量。
-
原子性同时约束知识点和各平台
claim;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,answerExcerpt可以复用原句。 -
仅个别平台提出的实质新增事实也要单独成点,其他平台标为未覆盖;不得把新增事实并入宽泛知识点后借用深知晓锚点免查。
-
同一事实的不同数值或条件放在同一知识点下,不拆成两点。
-
direct采用最小充分原则:缺失后就没有直接回答用户明确所问内容;reference是背景、提醒、延伸或相邻业务信息。问全国时省市案例、问城市时区县细项均属于补充参考,除非用户明确询问地区差异;只问条件/门槛/比例时,奖励、流程、电话等不进入直接答案。 -
每个平台逐点写明主张、所附依据和来源忠实性。
-
有显式引用标记的平台,只能使用该回答实际标出的来源;不得从未标出的来源中补证。
-
无显式引用标记的平台,才可以在该平台完整原始来源集合中寻找依据。
-
只使用原始答案采集阶段已捕获的 URL 与正文,不搜索、不换链、不引入外部事实。
-
若确认深知晓该知识点使用可信搜索且所附官方证据支持同一个原子事实,可声明
trustedAnchor;锚点只能覆盖该事实变量,超出部分必须另起无锚点知识点,由下游可信搜索核验。 -
同一知识点若普通深知晓和深度溯源各自附有支持其主张的官方原文,必须全部保留到
trustedAnchor.claimEvidenceMap;后续权威核验直接复用,不得因追加搜索未召回同一材料而降为证据不足。 -
顶层必须生成
synthesisDraft:status固定为unverified,正文基于全部相关知识点合并并保留冲突、条件和缺口,basisKnowledgePointIds只能引用当前知识点。它是独立可交付的“综合草案(未核验)”,不能冒充权威最终答案。
第二步:验收并渲染
python3 scripts/knowledge_compare.py \
--input <run>/results.json \
--analysis <run>/comparison-analysis.json \
--output <run>/comparison.json
python3 scripts/render_comparison.py \
--results <run>/results.json \
--comparison <run>/comparison.json \
--output <run>/comparison.html
comparison.html 按实际平台数展示全部原始答案与来源、知识点对比概览和
“综合草案(未核验)”;下方展示逐知识点完整对照。
交付门禁
python3 tests/smoke_test.py
python3 "${CODEX_HOME:-$HOME/.codex}/skills/.system/skill-creator/scripts/quick_validate.py" .
What ships with it
13 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.
- references/acceptance-criteria.md 2.8 KB
- references/contracts.md 4.9 KB
- scripts/common.py 967 B runs code
- scripts/knowledge_compare.py 61 KB runs code
- scripts/policy_match.py 2.9 KB runs code
- scripts/render_comparison.py 21 KB runs code
- tests/citation_presence_test.py 180 B runs code
- tests/deepseek_reference_faithfulness_test.py 180 B runs code
- tests/fixtures/comparison-analysis.json 3.0 KB
- tests/fixtures/results.json 1.3 KB
- tests/model_judgment_test.py 3.6 KB runs code
- tests/requirements_scope_test.py 180 B runs code
- tests/smoke_test.py 76 KB runs code
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.
- 1mo ago Changed · +4 lines 925f4cc89122
- 1mo ago First seen · 60 lines · 79 tokens per session scan A 5add71ee98bb
fact-check-x-knowledge-compare is a skill published in the GitHub repository ASI2030/Fact-Check-X (4 stars, last pushed 8d ago), licensed Apache-2.0. It adds 79 tokens to every session and 1,180 once invoked, about $0.0003 per session on Opus 5.5. 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.
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