Skip to content
Back to skills

Agent 1

ASecurity

Build LLM agents using `tdx agent pull/push` with YAML/Markdown config. Covers agent.yml structure, tools (knowledge_base, agent, web_search, image_gen), @ref syntax, and knowledge bases. Use for TD AI agent development workflow.

  • 2 stars
  • 0 votes
  • 0 copies
  • 0 views
  • Added September 27, 2026
toolsbashsqltestingdatabase

Works with

  • cli

Security analysis

A100/100

Scanned September 27, 2026

npx -y skills add David-Li0406/meta-skill-evloving --skill agent-1 --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Agent 1?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Agent 1
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/david-li0406-agent-1/badge)](https://www.skillsdirectory.com/skills/david-li0406-agent-1)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: agent
description: Build LLM agents using `tdx agent pull/push` with YAML/Markdown config. Covers agent.yml structure, tools (knowledge_base, agent, web_search, image_gen), @ref syntax, and knowledge bases. Use for TD AI agent development workflow.
---

# tdx Agent - LLM Agent Development

Build and manage LLM agents using `tdx agent pull/push` with YAML/Markdown configuration files.

## Key Commands

```bash
# Pull project to local files (creates agents/{project}/)
tdx agent pull "My LLM Project"
tdx agent pull "My LLM Project" "Agent Name"  # Single agent

# Push local changes to TD
tdx agent push                                # Push all from current dir
tdx agent push ./agents/my-project/my-agent/  # Push single agent
tdx agent push --dry-run                      # Preview changes

# Clone project (for staging/production deployment)
tdx agent clone "Source Project" --name "New Project"
tdx agent clone ./agents/my-project/ --name "Prod" --profile production

# List/show agents
tdx agents                                    # List in current project
tdx agent show "Agent Name"

# Test agents with chat
tdx chat --agent "project/Agent Name" "Your message"
tdx chat --new --agent "project/Agent Name" "Start new conversation"
```

## Folder Structure

```
agents/{project-name}/
├── tdx.json                    # {"llm_project": "Project Name"}
├── {agent-name}/
│   ├── agent.yml               # Agent configuration
│   ├── prompt.md               # System prompt (markdown)
│   └── starter_message.md      # Optional multiline starter
├── knowledge_bases/
│   ├── {name}.yml              # Table-based KB (TD database)
│   └── {name}.md               # Text-based KB (plain text)
└── prompts/
    └── {name}.yml
```

## agent.yml

```yaml
name: Support Agent

model: claude-4-sonnet            # claude-4-sonnet, claude-4-haiku
temperature: 1                    # REQUIRED: must be 1 when reasoning_effort is set
max_tool_iterations: 5
reasoning_effort: medium          # none, minimal, low, medium, high (requires temperature: 1)

starter_message: Hello! How can I help?

tools:
  - type: knowledge_base
    target: '@ref(type: "knowledge_base", name: "support-kb")'
    target_function: SEARCH       # SEARCH, LOOKUP, READ_TEXT, LIST_COLUMNS
    function_name: search_kb
    function_description: Search support knowledge base

  - type: agent
    target: '@ref(type: "agent", name: "sql-expert")'
    target_function: CHAT
    function_name: ask_sql_expert
    function_description: Ask SQL expert for help
    output_mode: RETURN           # RETURN (default) or SHOW

  - type: web_search
    target: '@ref(type: "web_search_tool", name: "web-search")'
    target_function: SEARCH
    function_name: search_web
    function_description: Search the web

  - type: image_gen
    target: '@ref(type: "image_generator", name: "image-gen")'
    target_function: TEXT_TO_IMAGE
    function_name: generate_image
    function_description: Generate an image

variables:
  - name: customer_context
    target_knowledge_base: '@ref(type: "knowledge_base", name: "customers")'
    target_function: LOOKUP
    function_arguments: '{"query": "{{customer_id}}"}'

outputs:
  - name: resolution_status
    function_name: get_status
    function_description: Get resolution status
    json_schema: '{"type": "object", "properties": {"status": {"type": "string"}}}'
```

## Reference Syntax

All cross-resource references use `@ref(...)`:

```yaml
'@ref(type: "knowledge_base", name: "my-kb")'
'@ref(type: "agent", name: "my-agent")'
'@ref(type: "prompt", name: "my-prompt")'
'@ref(type: "web_search_tool", name: "web-search")'
'@ref(type: "image_generator", name: "image-gen")'
```

## Knowledge Bases

### Table-based (.yml) - Queries TD database

```yaml
name: Product Catalog
database: ecommerce_db
tables:
  - name: products
    td_query: select * from products
    enable_data: true
    enable_data_index: true
```

### Text-based (.md) - Plain text content

```markdown
---
name: Company FAQ
---

# Frequently Asked Questions

## Return Policy
We offer 30-day returns...
```

## Prompts

```yaml
name: greeting-prompt
agent: '@ref(type: "agent", name: "support-agent")'
system_prompt: |
  Generate a personalized greeting...
template: |
  Customer: {{customer_name}}
```

## Typical Workflow

```bash
# 1. Pull project
tdx agent pull "My Project"

# 2. Edit files locally (agent.yml, prompt.md, knowledge bases)

# 3. Preview changes
tdx agent push --dry-run

# 4. Push to TD
tdx agent push

# 5. Test with tdx chat
tdx chat --agent "My Project/My Agent" "Hello, test message"
```

## Testing Agents

Use `tdx chat` to test agents from the command line:

```bash
# Basic chat
tdx chat --agent "project-name/Agent Name" "Your question here"

# Start new conversation (clears history)
tdx chat --new --agent "project-name/Agent Name" "Fresh start"

# Continue existing conversation
tdx chat --agent "project-name/Agent Name" "Follow-up question"
```

## Extended Thinking (Reasoning)

To enable extended thinking/reasoning, you must set `temperature: 1`:

```yaml
# With reasoning enabled
model: claude-4-sonnet
temperature: 1                    # REQUIRED when using reasoning_effort
reasoning_effort: medium          # none, minimal, low, medium, high

# Without reasoning (flexible temperature)
model: claude-4-sonnet
temperature: 0.7                  # Can be any value 0-1
# reasoning_effort: omit or set to none
```

**Note:** If you get the error `temperature may only be set to 1 when thinking is enabled`, either:
1. Set `temperature: 1`, or
2. Remove the `reasoning_effort` field

## Related Skills

- **tdx-basic** - Core CLI operations and context management

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…