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 ZTE-AICloud/Co-OmniSpec --skill design-functiongit clone --depth 1 https://github.com/ZTE-AICloud/Co-OmniSpecWrote 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/zte-aicloud/co-omnispec/design-function)<a href="https://agentmods.dev/skills/zte-aicloud/co-omnispec/design-function"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/design-function/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/zte-aicloud/co-omnispec/design-function"><img src="https://agentmods.dev/badge/skills/zte-aicloud/co-omnispec/design-function.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00035 | $0.01948 |
| Opus 5.5 | $0.00014 | $0.00779 |
| Sonnet 5.5 | $0.00007 | $0.00390 |
| Haiku 4.5 | $0.00003 | $0.00195 |
Grade A, and why
design-function 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
design-function
使用时机
- 仅被
designskill 显式调用
功能定义
- 功能是支撑场景达成目标所需的业务能力,应从外部可观测行为的视角描述系统“能够提供什么能力”。
- 功能必须可落地: 能够映射为「输入/输出 + 触发条件/前置条件 + 主要步骤 + 失败处理与补偿策略」。在后续设计阶段再明确由哪些组件/模块分别承担职责。
- 不得将“实现细节/代码结构”当作功能;不得将“接口清单”当作功能本身。
注意事项:
- 将场景中的关键验收点映射到功能的外部可观测行为,确保每条功能都能回答:
- 触发条件/前置条件是什么
- 输入/输出是什么
- 主路径步骤是什么
- 关键失败处理与补偿策略是什么
- 对识别出的功能集合做一致性校验,避免后续重复建设或边界漂移:
- 去重与合并: 不同场景下语义等价的功能应复用同一条功能(必要时通过“适用范围/约束条件”表达差异),避免同义重复。
- 粒度校准: 避免抽象过度(难以验证、无法落到可测试行为)或细节过度(陷入实现层设计/代码结构);必要时对功能进行拆分或收敛,但保持其对外可观测性。
- 命名与术语对齐: 功能名称与描述使用
context.md中已对齐的术语,避免同一概念多种叫法。
指令
步骤1: 明确输入与上下文
- 场景: 读取
FEATURE_DIR/spec.md中的「场景」章节,明确本次需要支撑的业务目标与验收标准。 - 上下文文件: 优先读取
FEATURE_DIR/context.md,参考其中的:- 「相关功能文档」章节,作为既有功能的主要参考来源
- 架构分析、可复用模式、术语对齐、约束和假设
- 若
context_mode = evidence_first,优先消费on_demand.scope、on_demand.traceability、on_demand.risks、on_demand.evidence_gaps
步骤2: 分析既有功能的变更
基于步骤1输入与上下文,按「功能定义」识别并产出本次变更涉及的全部功能条目(含INSERT/MODIFY/DELETE/REFER),作为后续步骤的范围基线。
动作类型定义:
- MODIFY: 业务意图要求对既有功能的输入/输出、约束条件、步骤、失败处理、适用范围等进行调整或细化。
- INSERT:
- 理解既有功能,业务意图无法合理归属到任何既有功能条目,或现有功能的职责边界无法承载新增能力且保持可验证性。
- 不存在既有功能时,则新增所需功能。
- DELETE: 业务意图明确要求移除既有功能,且删除具有明确业务必要性、风险可控(必须给出充分、可追溯的理由与影响说明)。
- REFER: 既有功能已充分覆盖当前业务意图,无需修改内容,但需建立引用关系以支持后续影响分析与可追溯性。
on-demand 功能消费规则(仅 evidence_first 模式):
- 先从
on_demand.scope.direct_functions和on_demand.scope.indirect_functions建立功能基线(白名单)。 - 通过
on_demand.traceability将需求/场景映射到功能条目,优先判定 MODIFY/REFER,减少无依据 INSERT。 - 对每个功能条目,优先引用
${DOC_DIR}/on-demand/functions/*.md中可定位证据(入口、主流程、波及点、风险)。 - 未进入
scope且无证据链支撑的功能,不得纳入主设计范围(避免 scope creep)。 on_demand.risks/on_demand.evidence_gaps要体现在功能的失败处理、补偿策略或假设说明中。
兼容规则(default 模式):
- 若
context_mode = default或on_demand字段缺失,沿用原有逻辑,不阻塞功能设计。
步骤3: 按照以下模板生成「功能」章节内容
## 功能
### [INSERT/MODIFY/DELETE/REFER] - [功能ID] - [功能名称]
**来源场景**: [场景ID] - [场景名称]
变更原因: [分析业务意图对存量功能的影响;REFER 填写为无变更]
**功能描述**: [从对应场景的验收场景中提取,描述该功能需要实现的具体能力]
[功能具体内容]
[按照上述格式继续描述其他功能...]
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 First seen · 112 lines · 35 tokens per session scan A 74aaa059b8c1
design-function is a skill published in the GitHub repository ZTE-AICloud/Co-OmniSpec (57 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 1,948 once invoked, about $0.0001 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 2026-08-30.
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