AI Agent 实现 工作流
- 作者仓库星标 0
- 作者仓库 skills-registry
AI Agent Implementation Workflow
What This Skill Produces
Use this skill to implement or update agent behavior with stable contracts. The expected result is:
- explicit agent goal and decision boundaries
- predictable tool invocation flow
- schema-safe outputs for downstream consumers
- graceful fallback when tools/providers fail
- targeted tests or smoke checks proving behavior
When to Use
Use this skill when you need to:
- add a new agent workflow
- refine tool usage logic for an existing agent
- fix agent output/schema instability
- harden retry/fallback behavior in agent loops
- align agent behavior across CLI/API/UI surfaces
Common trigger phrases:
- "implement this agent behavior"
- "add tool-calling to the agent"
- "fix unstable agent responses"
- "make the agent robust"
- "agent output schema keeps breaking"
Procedure
Define contract first
- Lock input/output schema and required fields.
- Clarify what is best-effort vs required behavior.
Constrain tool boundaries
- List which tools can be called and for what reasons.
- Keep side-effecting actions explicit and auditable.
Implement minimal orchestration
- Prefer small deterministic control flow over deep branching.
- Make retries bounded and reason-aware.
Handle degraded mode intentionally
- Return actionable errors when hard requirements are missing.
- Use safe fallback only when it preserves contract meaning.
Verify behavior incrementally
- Add focused tests/smokes for primary path + fallback path.
- Confirm output schema is stable across paths.
Validate integration surface
- Ensure consuming endpoints/UI can parse new outputs.
- Avoid silent breaking changes in event/JSON structure.
Quality Checks
Before finishing, confirm that:
- output schema is deterministic and documented
- tool usage boundaries are explicit
- retries/fallbacks are bounded and observable
- failures are actionable, not silent
- integration consumers remain compatible
<!-- tomevault:4.0:skill_md:2026-05-23 -->Source: Bryan-Roe/Aria — distributed by TomeVault.
- 流狐分类
- AI 智能
- 作者声明 Agent
- 未找到明确声明；不据此推断已兼容或已测试
- 静态检查
- 88 / 100 · 启发式扫描，不代表运行安全
- 作者 / 版本 / 许可
- @tomevault-io · 未声明 license
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 即装即用
- 是否需要外部 API Key
- 未发现要求
- 检测到的系统要求
- 未声明
- 底层运行要求
- 未声明
- 检测到的文件与系统行为
-
- 只读
- 允许写入 / 修改
- 检测到的网络行为
- 仅限本地
- 安装命令数
- 无（仅作为资料）
档案由构建时根据 SKILL.md 与安装命令自动衍生，可能与作者实际意图存在差异。
需要注意： 未限定 allowed-tools，默认拥有全部工具权限。
作者没有在当前 SKILL.md 中定义固定输出样例。 What This Skill Produces
Use this skill to implement or update agent behavior with stable contracts. The expected result is: explicit agent goal and decision boundaries predictable tool invocation flow
When to Use
Use this skill when you need to: add a new agent workflow refine tool usage logic for an existing agent
Procedure
Define contract first Lock input/output schema and required fields. Clarify what is best-effort vs required behavior.
Quality Checks
Before finishing, confirm that: output schema is deterministic and documented tool usage boundaries are explicit
# AI Agent Implementation Workflow
## What This Skill Produces
Use this skill to implement or update agent behavior with stable contracts. The expected result is:
- explicit agent goal and decision boundaries
- predictable tool invocation flow
- schema-safe outputs for downstream consumers
- graceful fallback when tools/providers fail
- targeted tests or smoke checks proving behavior
## When to Use
Use this skill when you need to:
- add a new agent workflow
- refine tool usage logic for an existing agent
- fix agent output/schema instability
- harden retry/fallback behavior in agent loops
- align agent behavior across CLI/API/UI surfaces
Common trigger phrases:
- "implement this agent behavior"
- "add tool-calling to the agent"
- "fix unstable agent responses"
- "make the agent robust"
- "agent output schema keeps breaking"
## Procedure
1. Define contract first
- Lock input/output schema and required fields.
- Clarify what is best-effort vs required behavior.
2. Constrain tool boundaries
- List which tools can be called and for what reasons.
- Keep side-effecting actions explicit and auditable.
3. Implement minimal orchestration
- Prefer small deterministic control flow over deep branching.
- Make retries bounded and reason-aware.
4. Handle degraded mode intentionally
- Return actionable errors when hard requirements are missing.
- Use safe fallback only when it preserves contract meaning.
5. Verify behavior incrementally
- Add focused tests/smokes for primary path + fallback path.
- Confirm output schema is stable across paths.
6. Validate integration surface
- Ensure consuming endpoints/UI can parse new outputs.
- Avoid silent breaking changes in event/JSON structure.
## Quality Checks
… 证据边界与执行链路
作者原文负责流程事实；流狐只索引当前章节、要点、文件与命令。
章节 -> What This Skill Produces → When to Use → Procedure → Quality Checks
要点 -> Use this skill to implement or update agent behavior with stable contracts. · 1. Define contract first - Lock input/output schema and required fields. · 2. Constrain tool boundaries - List which tools can be called and for what reasons. · 3. Implement minimal orchestration - Prefer small deterministic control flow over deep branching. · 4. Handle degraded mode intentionally - Return actionable errors when hard requirements are missing. · 5. Verify behavior incrementally - Add focused tests/smokes for primary path + fallback path. · 6. Validate integration surface - Ensure consuming endpoints/UI can parse new outputs. · --- > Source: [Bryan-Roe/Aria](https://github.com/Bryan-Roe/Aria) — distributed by [TomeVault](https://tomevault.io).
文件/命令 -> tools/providers · output/schema · retry/fallback · CLI/API/UI · input/output · tests/smokes · endpoints/UI · event/JSON
内容 SHA-256 -> 955dfe675356
原文结构
适用与边界
原文中的明确线索
tools/providers、output/schema、retry/fallback、CLI/API/UI、input/output、tests/smokes、endpoints/UI、event/JSON