desirecore/market
2
0
Fork 0
mirror of https://git.openapi.site/https://github.com/desirecore/market.git synced 2026-07-23 05:43:48 +08:00
Code Issues Packages Projects Releases Wiki Activity

docs(discover-agent): 使用场景补充"更换智能体"情形 (#40)

Browse Source 
给 discover-agent 的中文源补充一条使用场景。

同时这是 #39(pull_request_target 自动翻译流水线)的端到端验证 PR:中文源变更 → en-US 过期 → CI
应自动翻译并把 commit 推回本分支、发评论。

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: desirecore-bot <bot@desirecore.net>
This commit is contained in:
yi-ge
2026-07-07 20:04:55 +08:00
committed by GitHub
parent 48402cf62f
commit b273a1008a
2 changed files with 109 additions and 107 deletions
Download Patch File Download Diff File Expand all files Collapse all files

215
skills/discover-agent/SKILL.md
View File

@@ -28,13 +28,13 @@ metadata:
translated_by: human
en-US:
name: Discover Agent
short_desc: Intelligently recommend the best-matching Agent based on the user's needs and guide a quick selection
short_desc: Intelligently recommend the best-matching Agent based on the user’s need description, and guide quick selection
description: >-
Recommend the best-matching Agent based on the user's needs, present a candidate list, and guide the user's selection. Use when the user describes a need but is unsure which Agent to ask, or wants to browse available Agents.
Recommend the best-matching Agent based on the user’s needs, show a candidate list, and guide selection. Use when the user describes a need but is unsure which Agent to ask for help, or wants to browse available Agents.
body: ./SKILL.md
source_hash: sha256:28ecd07724adda9a
translated_by: ai:claude-opus-4-7
translated_at: '2026-05-03'
source_hash: sha256:4be238743dee6fc4
translated_by: ai:openai:gpt-5.4-mini
translated_at: '2026-07-07'
market:
icon: >-
<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0
@@ -55,34 +55,35 @@ market:
channel: latest
---
# discover-agent skill
# discover-agent Skill
## L0: One-Sentence Summary
## L0: One-sentence summary
Match and recommend the most suitable registered Agent based on the user's described needs.
Match and recommend the most suitable Agent from the registered Agents based on the user’s needs.
## L1: Overview and Use Cases
## L1: Overview and use cases
### Capability Description
### Capability description
discover-agent is a **Procedural Skill** that gives DesireCore the ability to discover and recommend a suitable Agent for the user. It understands the user's described needs, performs multi-dimensional matching across the registered Agent list, and presents a candidate list for the user to choose from.
discover-agent is a **procedural Skill** that gives DesireCore the ability to discover and recommend suitable Agents for users. By understanding the user’s needs, it performs multi-dimensional matching across the registered Agent list and shows a candidate list for the user to choose from.
### Use Cases
### Use cases
- The user describes a need but doesn't know which Agent to ask for help
- The user wants to browse currently available Agents and their capabilities
- The user needs to find the best specialist assistant for a specific task
- A new user trying the system for the first time needs to learn which Agents are available
- The user describes a need but does not know which Agent to ask for help
- The user wants to browse the currently available Agents and their capabilities
- The user needs to find the most suitable specialist assistant for a specific task
- A new user is using the system for the first time and needs to know which Agents are available
- The user is unhappy with the current Agent’s performance and wants a better alternative
### Core Value
### Core value
- **Lower the barrier**: Users don't have to remember each Agent's name and capabilities
- **Precise matching**: Smart recommendations based on the semantics of the need, not simple keyword search
- **Smooth handoff**: When there's no match, automatically suggest creating a new Agent (handing off to the create-agent skill)
- **Lower the barrier**: Users do not need to remember each Agent’s name and capabilities
- **Precise matching**: Intelligent recommendations based on semantic needs, not simple keyword search
- **Smooth handoff**: If no match is found, automatically suggest creating a new Agent (handoff to the create-agent Skill)
## L2: Detailed Specification
## L2: Detailed specification
### Execution Flow
### Execution flow
```
┌──────────────┐ ┌──────────────┐ ┌──────────────┐
@@ -95,29 +96,29 @@ discover-agent is a **Procedural Skill** that gives DesireCore the ability to di
└──────────────┘ └──────────────┘ └──────────────┘
```
### Stage 1: Need Understanding
### Stage 1: Needs understanding
**Trigger conditions** (any one is sufficient):
**Trigger conditions** (any one of the following):
- The user says "find me a...", "is there a...", "who can help me..."
- The user describes a task without specifying a particular Agent
- The user says "what Agents are there?", "show me who's available"
- The system detects that the user's need does not match the current Agent's capabilities
- The user says "帮我找一个...", "有没有...", or "谁能帮我..."
- The user describes a task but does not specify a particular Agent
- The user says "有哪些智能体" or "看看都有谁"
- The system detects that the user’s need does not match the current Agent’s capabilities
**Need parsing**:
Extract the following dimensions from the user's description:
Extract the following dimensions from the user’s description:
| Dimension | Description | Examples |
| ----------- | ----------------- | --------------------------------------- |
| `domain` | Specialty domain | Legal, finance, technology, education |
| `task_type` | Task type | Consultation, review, analysis, writing |
| `keywords` | Keywords | Contract, report, code, paper |
| `urgency` | Urgency level | Routine / urgent |
| Dimension | Description | Example |
| --------- | ----------- | ------- |
| `domain` | Professional domain | law, finance, technology, education |
| `task_type` | Task type | consultation, review, analysis, creation |
| `keywords` | Keywords | contract, report, code, paper |
| `urgency` | Urgency | routine / urgent |
### Stage 2: Agent Retrieval
### Stage 2: Agent retrieval
**Data source**: Call `GET /api/agents` to fetch the list of all registered Agents.
**Data source**: Call `GET /api/agents` to get the list of all registered Agents.
**API call**:
@@ -127,48 +128,48 @@ GET /api/agents
**Key fields in the returned data**:
- `id` — Unique Agent identifier
- `id` — unique Agent identifier
- `name` — Agent name
- `description` — Agent description
- `skills` — Skill list
- `status` — Current status (online/offline/busy)
- `status` — current status (online/offline/busy)
**Filter rules**:
**Filtering rules**:
- By default, show only Agents with `status: online` or `status: offline`
- Exclude system-internal Agents (e.g. DesireCore itself, unless the user explicitly requests them)
- By default, only show Agents with `status: online` or `status: offline`
- Exclude internal system Agents (such as DesireCore itself, unless explicitly requested by the user)
### Stage 3: Match Evaluation
### Stage 3: Matching evaluation
Comprehensively judge match degree based on the following dimensions (using LLM semantic understanding rather than formula-based computation):
Evaluate the match score based on the following dimensions (using LLM semantic understanding, not formula-based calculation):
| Dimension | Description |
| ---------------------- | ------------------------------------------------------------------------ |
| Description relevance | Semantic relevance between Agent description / persona and user's need |
| Skill match | Relevance of the Agent's skills to the task type |
| Domain fit | Fit between the Agent's specialty domain and the user's need domain |
| Status availability | Agent's current status (online preferred over offline) |
| Dimension | Description |
| --------- | ----------- |
| Description relevance | Semantic relevance between the Agent’s description / persona and the user’s need |
| Skill match | Correlation between the Agent’s skills and the task type |
| Domain fit | Degree of fit between the Agent’s professional domain and the user’s domain |
| Status availability | The Agent’s current status (online takes priority over offline) |
**Display rules**:
- Highly matched (clearly suited to the task) → tag as "Recommended"
- Partial match (may help) → tag as "Possibly relevant"
- No clear relation → do not display
- High match (clearly suitable for the task) → mark as "推荐"
- Partial match (may be helpful) → mark as "可能相关"
- No obvious relevance → do not display
### Stage 4: Candidate Ranking
### Stage 4: Candidate ranking
**Ranking rules**:
1. Sort by overall score in descending order
2. On ties, online status takes precedence
2. If scores are tied, prefer online status
3. Show at most 5 candidates
### Stage 5: Result Display
### Stage 5: Result display
**When matches are found**:
**When there are matching results**:
```
根据你的需求，我推荐以下智能体：
Based on your needs, I recommend the following Agents:
┌─────────────────────────────────────────────────────┐
│ 1. 法律顾问助手 匹配度: 92% │
@@ -187,79 +188,79 @@ Comprehensively judge match degree based on the following dimensions (using LLM
│ 状态：离线 │
└─────────────────────────────────────────────────────┘
请选择一个智能体，或告诉我更具体的需求。
Please choose an Agent, or tell me more specific requirements.
```
**When no matches are found**:
**When there are no matching results**:
```
目前没有找到完全匹配你需求的智能体。
No fully matching Agent was found for your needs at the moment.
你可以：
1. 用更具体的描述再试一次
2. 创建一个新的专业智能体（我可以帮你）
3. 浏览所有可用的智能体
You can:
1. Try again with a more specific description
2. Create a new specialist Agent (I can help you)
3. Browse all available Agents
你想怎么做？
What would you like to do?
```
**Browse mode** (when the user asks to view all):
```
当前可用的智能体：
Currently available Agents:
在线：
Online:
- 法律顾问助手 — 合同审查和法律风险评估
- AI 文书助手 — 专业文书撰写和格式优化
离线：
Offline:
- 数据分析师 — 数据分析和可视化报告
- 翻译助手 — 多语言翻译和本地化
共 4 个智能体。需要了解某个智能体的详细信息吗？
A total of 4 Agents. Do you need detailed information about any one Agent?
```
### Stage 6: Guided Selection
### Stage 6: Guidance and selection
**Actions after the user selects**:
**Actions after the user makes a choice**:
| User Choice | Follow-up Action |
| ------------------------ | ------------------------------------------------------------------ |
| Selected an Agent | Switch to a conversation with that Agent and pass the need context |
| Asked to learn more | Call `GET /api/agents/:id` for details and present structured info (see below) |
| Not satisfied with candidates | Guide the user to refine the need or suggest creating a new Agent |
| Chose "create new" | Invoke the create-agent skill, passing the need info already collected |
| User choice | Follow-up action |
| ----------- | ---------------- |
| Chose an Agent | Switch to that Agent’s conversation and pass the user need context |
| Asked for more details | Call `GET /api/agents/:id` to get details, then show structured information (see below) |
| Unsatisfied with candidates | Guide the user to refine the need or suggest creating a new Agent |
| Chose "create a new one" | Call the create-agent Skill and pass the collected need information |
**Implementation of "learn more"**:
Call `GET /api/agents/:id` for details, and optionally call structured endpoints for persona/principles:
Call `GET /api/agents/:id` to get details, and optionally call the structured endpoint to get persona/rules:
```bash
# 获取基本信息
# Get basic information
GET /api/agents/{agentId}
# 返回: { id, name, description, skillsCount, toolsCount, status, config, persona, principles }
# Return: { id, name, description, skillsCount, toolsCount, status, config, persona, principles }
# 获取结构化 persona（可选，用于展示更丰富的信息）
# Get structured persona (optional, used to show richer information)
GET /api/agents/{agentId}/persona
# 返回: { L0, L1: { role, personality, communication_style }, L2 }
# Return: { L0, L1: { role, personality, communication_style }, L2 }
```
When presenting to the user, render key information in natural language / table form:
When presenting to the user, show key information in natural language/table format:
```
「法律顾问助手」详细信息
| 字段 | 内容 |
|------|------|
| 角色定位 | 专注合同审查和法律风险评估 |
| 性格特征 | 专业、严谨、审慎 |
| 技能数量 | 3 个 |
| 当前状态 | 在线 |
| Role positioning | 专注合同审查和法律风险评估 |
| Personality traits | 专业、严谨、审慎 |
| Skill count | 3 个 |
| Current status | 在线 |
需要与这个智能体对话吗？
Need to talk with this Agent?
```
**Context handoff on switch**:
**Context handoff**:
```yaml
context_handoff:
@@ -268,29 +269,29 @@ context_handoff:
user_intent: '帮我审查这份合同的风险点'
```
### Collaboration with Other Skills
### Collaboration with other Skills
| Collaborating Skill | How It Collaborates |
| ------------------- | ----------------------------------------------------------- |
| create-agent | When there's no match, suggest creating a new Agent and pass the user's need as initial info |
| task-management | After a successful match, optionally auto-create a task and assign it to the target Agent |
| Collaboration Skill | Collaboration method |
| ------------------- | -------------------- |
| create-agent | When there is no match, suggest creating a new Agent and pass the user need as initial information |
| task-management | After a successful match, tasks can be created automatically and assigned to the target Agent |
### Error Handling
### Error handling
| Error Scenario | Handling |
| ---------------------------- | --------------------------------------------------------- |
| API call fails | Indicate a network error and suggest retrying later |
| Agent list is empty | Guide the user to create their first Agent |
| User description too vague | Ask follow-up questions and offer domain options to guide |
| Recommended Agent has bad status | Mark the status and suggest selecting another online Agent |
| Error scenario | Handling method |
| -------------- | --------------- |
| API call failure | Prompt a network error and suggest trying again later |
| Agent list is empty | Guide the user to create the first Agent |
| User description is too vague | Ask follow-up questions and provide domain options as guidance |
| Recommended Agent has an abnormal status | Mark the status and suggest choosing another online Agent |
### Permission Requirements
### Permission requirements
- Prefer accessing the Agent Service HTTP API via the `Bash` tool with curl
- The API base URL is already injected into the "Local API" section of the system prompt; reference it directly
- Read-only operations; no risk
- Prefer using the `Bash` Tool to call curl and access the Agent Service HTTP API to complete operations
- The API base address is injected into the system prompt’s "本机 API" section, so reference it directly
- Read-only operation, no risk
### Dependencies
- Agent Service HTTP API (`GET /api/agents`)
- The local API URL declaration in the system prompt
- The local API address declaration in the system prompt