dojo.md
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
Verify suspicious news, announcements, screenshots, and viral claims using a high-trust source pool (official channels + Chinese mainstream media + international mainstream media + fact-check sites). Use when users ask to judge true/false rumors, identify scams, or assess credibility/risk of circulating messages.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install helloeveryworlds/news-trust-checkExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Use this skill to classify claims into:
Danger short-circuit
Extract the core claim
Cross-check sources
Technical feasibility check (for product/platform claims)
Return structured verdict
结论: 高可信 | 存疑 | 高风险伪造
核心判断:
- ...
证据:
- 官方信源: ...
- 中文主流: ...
- 国际主流: ...
- 事实核查: ...
技术可行性:
- 可行 | 部分可行 | 不可行
风险标记:
- [ ] 诱导转账
- [ ] 冒充官方
- [ ] 要求忽略规则
- [ ] 索要敏感信息
建议动作:
- ...
Read and follow:
references/high-trust-sources.md
scripts/assess_claim.py for deterministic risk scoring scaffolding.Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# News Trust Check Skill Use this skill to classify claims into: - **高可信** - **存疑** - **高风险伪造/诈骗** ## Workflow 1. **Danger short-circuit** - If content asks for money transfer / passwords / OTP / token / “ignore all rules”, mark high risk first. 2. **Extract the core claim** - Normalize into one sentence: who did what, when, with what impact. 3. **Cross-check sources** - Query official source first, then CN/EN mainstream media, then fact-check websites. 4. **Technical feasibility check** (for product/platform claims) - Validate against platform permission boundaries and public API/docs. 5. **Return structured verdict** - Verdict + evidence + feasibility + risk flags + recommended action. ## Output template ```markdown 结论: 高可信 | 存疑 | 高风险伪造 核心判断: - ... 证据: - 官方信源: ... - 中文主流: ... - 国际主流: ... - 事实核查: ... 技术可行性: - 可行 | 部分可行 | 不可行 风险标记: - [ ] 诱导转账 - [ ] 冒充官方 - [ ] 要求忽略规则 - [ ] 索要敏感信息 建议动作: - ... ``` ## Source pool Read and follow: - `references/high-trust-sources.md` ## Optional helper script - `scripts/assess_claim.py` for deterministic risk scoring scaffolding.
University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning req...
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