Skills Overview

The skill definition on this page is adapted from the Agent Skills description, which frames skills as lightweight, self-contained capability packages that agents can discover, load, and apply on demand.

What is a skill?

In DB-GPT, a skill is a reusable capability package that gives an agent a structured way to solve a task.

Instead of relying only on free-form reasoning, a skill provides a stable execution pattern for a specific kind of work.

Skill definition

Adapted from the Agent Skills description, a skill can be understood as:

• a lightweight extension format for giving agents specialized knowledge and workflows
• a package of know-how, not just facts, APIs, or prompts
• a progressive-disclosure unit that can be discovered first and fully loaded only when needed
• a self-contained bundle of instructions, scripts, templates, and reference files
• a way to make agent behavior more consistent, repeatable, and domain-aware

In DB-GPT terms, a skill is not just “something the model knows.” It is a packaged workflow that helps the agent decide:

• what problem it is solving
• what tools it should use
• what order the steps should follow
• what outputs should be produced
• what constraints it should obey

What a skill usually contains

A DB-GPT skill package often includes:

• a name
• instructions in SKILL.md
• optional scripts
• optional templates
• optional static resources or examples

At its core, a skill is a folder containing a SKILL.md file. This file includes metadata and instructions that tell an agent how to perform a specific task. Skills can also bundle scripts, templates, and reference materials.

my-skill/
├── SKILL.md          # Required: instructions + metadata
├── scripts/          # Optional: executable code
├── references/       # Optional: documentation loaded as needed
└── assets/           # Optional: templates, output resources, static files

Skill anatomy

Following the structure used by DB-GPT's own skill-creator guidance, a skill is organized as a small self-contained package:

Part	Required	Purpose
SKILL.md	Yes	Defines the skill's identity and instructions
scripts/	No	Stores executable code such as Python or shell helpers
references/	No	Stores documents that can be loaded into context only when needed
assets/	No	Stores templates, fonts, icons, boilerplate files, or other output resources

SKILL.md

SKILL.md is the entry point of the skill. It usually contains:

• metadata such as name and description
• the workflow instructions the agent should follow
• guidance on when to read additional references or use bundled resources

scripts/

Use scripts/ for executable helpers, such as:

• Python data-processing utilities
• shell scripts
• report-generation helpers
• automation code used by the skill

references/

Use references/ for supporting knowledge that should not always live inside SKILL.md, such as:

• API documentation
• business logic references
• schemas
• workflow guides
• policy or domain documents

This keeps SKILL.md smaller while still making deeper context available when the task requires it.

assets/

Use assets/ for files that support the output rather than the reasoning process, such as:

• HTML templates
• icons and logos
• fonts
• boilerplate frontend files
• report resources

Why skills matter

Skills are useful when:

• a workflow should be standardized
• the task requires domain-specific reasoning
• reporting or analysis should follow a known pattern
• the agent should use curated instructions instead of improvising everything

How skills work

The common execution pattern is:

1. The agent identifies that a task matches a skill.
2. The skill instructions are loaded.
3. The agent follows the skill-defined workflow.
4. The required tools are executed.
5. The final answer, report, or page is returned.

Skills and built-in tools

Skills often orchestrate the built-in execution tools together:

• load_skill → load the skill instructions
• sql_query → retrieve structured data if needed
• code_interpreter → compute metrics, transform data, and generate charts
• shell_interpreter → run shell commands when required
• html_interpreter → render the final report or webpage

Practical examples

Financial report analysis

A financial-report skill can define:

• how to inspect uploaded reports
• how to compute indicators and compare periods
• how to generate charts and summaries
• how to render the final HTML report

CSV / Excel analysis

A data-analysis skill can define:

• how to inspect a dataset
• how to calculate core metrics
• how to visualize outputs
• how to turn the result into a reusable report

Good practices

• use skills when the workflow should be repeatable
• follow the skill instructions strictly
• prefer the tools required by the skill over ad-hoc alternatives
• use html_interpreter for final report rendering when the skill produces a webpage or report

Next step

See How to Use Skill for the practical workflow.