TalkCody

Agent Configuration

Advanced configuration for AI agents

Agent Configuration

Advanced settings for configuring and managing AI agents in TalkCody.

Overview

Agent configuration allows you to:

  • Fine-tune agent behavior
  • Manage tool permissions
  • Configure dynamic prompts
  • Set agent-specific parameters
  • Control agent visibility and defaults

Agent Settings

Basic Configuration

Agent Name

  • Unique identifier for the agent
  • Appears in agent selector
  • Should be descriptive (e.g., "React Expert", "Python Debugger")

Description

  • Optional longer explanation
  • Helps identify agent purpose
  • Shown in agent list and tooltips

Agent Type

  • User Agent: Visible to users, selectable in chat
  • System Agent: Hidden, used internally
  • Template Agent: Starting point for new agents

System Prompt

The system prompt is the most important configuration.

Structure:

[Role Definition]
You are a [role] specialized in [domain].

[Behavior Guidelines]
When [condition]:
1. [Action 1]
2. [Action 2]
3. [Action 3]

[Output Format]
Respond using this format:
- [Format specification]

[Constraints]
Always:
- [Requirement 1]
- [Requirement 2]

Never:
- [Restriction 1]
- [Restriction 2]

Best practices:

  • Be specific and concrete
  • Include examples
  • Define expected output format
  • List both requirements and restrictions
  • Keep under 1000 words for efficiency

Dynamic Prompts

Use variables that get replaced at runtime:

Available variables:

{project_name}      - Current project name
{language}          - Primary programming language
{framework}         - Main framework
{file_path}         - Current file being edited
{file_type}         - File extension
{timestamp}         - Current date/time
{user_name}         - User's name
{workspace_path}    - Project directory path

Example:

You are a {language} expert working on the {project_name} project.

Current context:
- Framework: {framework}
- File: {file_path}
- Time: {timestamp}

Provide {language}-specific advice following {framework} best practices.

When to use:

  • Multi-project workflows
  • Language-specific agents
  • Context-dependent behavior
  • Time-based responses

Dynamic prompts make agents more versatile and context-aware.

Model Configuration

Default Model

Assign specific model to agent:

Options:

  • Use Global Default: Inherits from general settings
  • Specific Model: Always use assigned model
  • User Choice: Let user select per conversation

Recommendations:

Code Generator → Qwen 3 Coder
Code Reviewer → Claude 4.5 Sonnet
Quick Helper → Claude Haiku
Documentation → GPT-4.1
Test Writer → Claude 4.5 Sonnet
Bug Finder → Claude 4.5 Opus

Model Parameters

Override global settings per agent:

Temperature

Code Generator: 0.2 (deterministic)
Creative Writer: 0.9 (varied)
General Helper: 0.7 (balanced)

Max Tokens

Quick Answers: 512 tokens
Normal: 2048 tokens
Long-form: 4096+ tokens

Custom Parameters

  • Top P
  • Frequency Penalty
  • Presence Penalty
  • Stop Sequences

Tool Configuration

Tool Permissions

Control which tools each agent can use:

File Tools

  • Read File: Safe, usually enable
  • ⚠️ Write File: Consider per agent
  • ⚠️ Edit File: Consider per agent
  • Delete File: Rarely needed

Search Tools

  • Code Search: Usually safe
  • File Search: Usually safe
  • ⚠️ Web Search: May slow responses

Execution Tools

  • ⚠️ Bash Tool: Powerful but risky
  • ⚠️ Web Crawl: May be slow

Agent Tools

  • Call Agent: Enable for workflows
  • Todo Write: Useful for planning

MCP Tools

  • Configure per MCP server
  • Enable selectively
  • Consider security implications

Tool Configuration Examples

Read-Only Analyst

✅ Read File
✅ Code Search
✅ File Search
❌ Write File
❌ Edit File
❌ Delete File
❌ Bash Tool

Code Generator

✅ Read File
✅ Write File
✅ Edit File
❌ Delete File
✅ Code Search
❌ Bash Tool

Full-Access Assistant

✅ All file tools
✅ All search tools
✅ Bash Tool (with confirmation)
✅ Web tools
✅ MCP tools

Tool Behavior Settings

Confirmation Requirements

File Write: Always confirm
File Edit: Confirm for >10 lines
File Delete: Always confirm
Bash Execution: Always confirm

Tool Timeouts

File Operations: 5s
Code Search: 10s
Web Crawl: 30s
Bash Commands: 60s

Tool Limits

Max Files to Read: 10 per request
Max Search Results: 100
Max Bash Output: 10KB

Output Configuration

Output Format

Define how agent responses should be structured:

Markdown Templates

## Summary
[Brief overview]

## Analysis
[Detailed analysis]

## Recommendations
1. [Recommendation 1]
2. [Recommendation 2]

## Code Examples
```[language]
[Code here]
```

JSON Responses

For structured data requests, respond in JSON:
{
  "status": "success|error",
  "data": { ... },
  "message": "..."
}

Code-Only Mode

For code generation requests:
- Provide only code, no explanations
- Include brief inline comments
- No markdown, just the code

Language Settings

Response Language

Settings → Agent → Response Language
Options: English, Chinese, Japanese, etc.

Code Style

Indentation: 2 spaces / 4 spaces / tabs
Quote Style: single / double
Semicolons: always / never / auto
Trailing Commas: always / never / es5

Advanced Features

Agent Chaining

Configure agents to call other agents:

Enable Chaining

Settings → Agent → Enable Agent Calls

Chain Configuration

Agent: Planner
Can Call: [Code Generator, Test Writer, Reviewer]
Max Chain Depth: 3

Example workflow:

1. Planner Agent breaks down task
2. → Calls Code Generator for implementation
3. → Calls Test Writer for tests
4. → Calls Reviewer for validation
5. Returns complete solution

Chain limits:

  • Max depth: 5 levels
  • Max calls: 10 per chain
  • Timeout: 300s per chain

Context Management

Message History

Include in Context:
○ All messages
● Last 10 messages
○ Last N tokens
○ Smart compression

File Context

Auto-include:
☑ Current open file
☐ Related files
☐ Recently edited files
☐ Files mentioned in conversation

Project Context

☑ Project name and path
☑ Primary language
☑ Framework information
☐ All package.json/dependencies
☐ README content

Conditional Behavior

Define behavior based on conditions:

File Type Rules

IF file_type == ".ts" OR file_type == ".tsx":
  Use strict TypeScript types
  Suggest React patterns

IF file_type == ".py":
  Follow PEP 8
  Use type hints

Project Rules

IF framework == "React":
  Suggest functional components
  Recommend hooks over classes

IF framework == "Vue":
  Use Composition API
  Follow Vue style guide

Agent Templates

Creating Templates

Save agent configurations as templates:

  1. Configure agent completely
  2. Click Save as Template
  3. Name the template
  4. Template available for new agents

Use cases:

  • Team standardization
  • Quick agent creation
  • Best practice sharing

Importing/Exporting

Export Agent

{
  "name": "Python Expert",
  "systemPrompt": "...",
  "model": "claude-4.5-sonnet",
  "temperature": 0.7,
  "tools": ["readFile", "writeFile", "codeSearch"],
  "maxTokens": 2048
}

Share with team:

  1. Export agent to JSON
  2. Share file with team
  3. Team members import
  4. Consistent agent across team

Agent Management

Agent Organization

Folders/Categories

📁 Code Assistants
  - Python Expert
  - JavaScript Pro
  - Rust Developer

📁 Reviewers
  - Code Reviewer
  - Security Auditor
  - Performance Analyzer

📁 Specialists
  - Test Generator
  - Documentation Writer
  - API Designer

Agent Versioning

Track agent changes:

  • Enable version history
  • Compare versions
  • Rollback to previous
  • Export specific version

Default Agent

Set default agent for:

  • New Conversations: Auto-selected
  • File Type: Different defaults per language
  • Project: Project-specific defaults
Default: General Assistant
TypeScript files: TypeScript Expert
Python files: Python Expert
Test files: Test Helper

Performance Optimization

Response Speed

For faster agents:

  • Use fast models (Haiku, GPT-4.1 Turbo)
  • Reduce max tokens
  • Limit tool access
  • Minimize system prompt

Cost Optimization

For cheaper agents:

  • Use budget models
  • Lower max tokens
  • Enable smart compression
  • Reduce tool calls

Quality vs Speed

Balanced configuration:

Quick Tasks: Claude Haiku, 512 tokens
Normal: Claude 4.5 Sonnet, 2048 tokens
Complex: Claude 4.5 Opus, 4096 tokens

Troubleshooting

Agent Not Following Instructions

Solutions:

  • Make system prompt more explicit
  • Add examples of desired behavior
  • Try different model (Claude often better)
  • Reduce prompt complexity
  • Test iteratively

Agent Using Wrong Tools

Check:

  • Tool permissions in config
  • System prompt mentions tools correctly
  • Tool confirmations are enabled
  • MCP tools are accessible

Inconsistent Behavior

Causes:

  • Temperature too high
  • Dynamic variables not resolving
  • Model switching
  • Context not maintained

Fixes:

  • Lower temperature
  • Verify variable syntax
  • Pin to specific model
  • Check context settings

Next Steps

Well-configured agents dramatically improve productivity. Take time to optimize your agent setup!