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 SuperChason/ontology-driven-ai-data-management-skills --skill scenario-related-knowledge-structuregit clone --depth 1 https://github.com/SuperChason/ontology-driven-ai-data-management-skillsWrote 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/superchason/ontology-driven-ai-data-management-skills/scenario-related-knowledge-structure)<a href="https://agentmods.dev/skills/superchason/ontology-driven-ai-data-management-skills/scenario-related-knowledge-structure"><img src="https://agentmods.dev/badge/skills/superchason/ontology-driven-ai-data-management-skills/scenario-related-knowledge-structure/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/superchason/ontology-driven-ai-data-management-skills/scenario-related-knowledge-structure"><img src="https://agentmods.dev/badge/skills/superchason/ontology-driven-ai-data-management-skills/scenario-related-knowledge-structure.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 | $0.00102 | $0.01038 |
| Opus 5 | $0.00051 | $0.00519 |
| Sonnet 5 | $0.00020 | $0.00208 |
| Haiku 4.5 | $0.00010 | $0.00104 |
Grade A, and why
scenario-related-knowledge-structure 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.
What it actually says
场景相关的知识结构
方法骨架
- 围绕已确认的 Agent 任务，组织完成任务所需的知识领域、来源、证据、责任和复用资产。
- 制度、流程、数据、模型、案例和专家经验分别登记权威级别、版本、适用范围和可访问性。
- 本阶段可以发现候选对象、关系、规则和例外，正式定义统一进入场景语义模型。
- 同一业务结论存在多个来源时，保留差异并建立裁决责任，不自动合并成确定规则。
- 通过知识缺口判断哪些任务可继续、哪些只能样本验证、哪些需要暂停。
需要详细产物字段时读取 知识结构契约。
执行步骤
-
按任务建立知识需求
- 动作：为每项 Agent 判断和动作列出需要的定义、规则、流程、案例、权限和证据。
- 完成标准：知识需求能够追溯到具体任务。
-
盘点知识来源
- 动作：登记制度、文档、表单、数据、接口说明、规则模型、历史案例、专家和已有语义资产。
- 完成标准：每项来源有版本、责任、适用范围和访问状态。
-
组织知识领域与依赖
- 动作：按当前场景划分知识主题、上下游依赖和公共/领域/场景资产引用。
- 完成标准：能够判断哪些直接使用、哪些复用、哪些需要新建。
-
建立证据链
- 动作：把候选知识条目连接到具体来源位置、真实案例或专家确认记录。
- 完成标准：关键结论有证据或明确待确认状态。
-
处理冲突与缺口
- 动作：识别版本冲突、同名异义、口径差异、失效知识和没有责任人的空白。
- 完成标准：每个冲突有裁决人，每个缺口有任务影响和处理建议。
-
交付知识提取输入
- 动作：确定可进入 29 类知识提取的材料、专家和问题清单。
- 完成标准：提取范围、来源和确认机制明确。
固定输出
- 场景知识领域地图
- Agent 任务—知识需求矩阵
- 制度、文档、数据、模型、案例和专家来源台账
- 来源权威级别、版本、适用范围和责任人
- 公共、领域和场景资产复用清单
- 候选知识条目与证据索引
- 知识冲突、缺口、失效和待裁决清单
- 29 类知识提取的材料与访谈计划
使用边界
- 对象、术语、关系、约束、规则、状态、权限、动作和目标的权威定义由场景语义模型管理。
- 表字段物理位置由数据需求与准备度阶段管理；本阶段只引用其作为知识来源。
- 只有来源清单时不能声称知识已经正确提取或业务专家已经确认。
- 通用企业知识只按当前场景需要引用，验证出稳定复用价值后再向领域或公共层沉淀。
相关 Skills
depends-on→business-scenario-deep-analysis与scenario-data-requirements-readiness。feeds-into→twenty-nine-sentence-knowledge-extraction和scenario-related-semantic-modeling。
审计信息
- 首次公开版本：2026-08-31
- 来源说明：面向场景知识准备和证据治理独立整理。
What ships with it
4 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.
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 · 75 lines · 102 tokens per session scan A 33f8b80755b7
scenario-related-knowledge-structure is a skill published in the GitHub repository SuperChason/ontology-driven-ai-data-management-skills (10 stars, last pushed 5d ago), licensed MIT. It adds 102 tokens to every session and 1,038 once invoked, about $0.0005 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 2026-09-04.
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