> ## Documentation Index
> Fetch the complete documentation index at: https://docs.swarms.world/llms.txt
> Use this file to discover all available pages before exploring further.
# SkillsManager
> Loads Agent Skills from disk and renders them into an agent system prompt
## Overview
`SkillsManager` implements Agent Skills: `SKILL.md` files on disk, discovered and folded into an agent's system prompt. It supports the tiered loading model — name/description metadata kept in memory for context-aware activation (Tier 1), and a skill's full body pulled on demand (Tier 2).
Every `Agent` builds one automatically as `agent.skills`. It is also usable standalone.
```python theme={null}
from swarms import Agent
agent = Agent(agent_name="Analyst", skills_dir="./skills")
agent.run("Build a DCF model") # relevant skills load into the prompt
```
## Import
```python theme={null}
from swarms.agents.skills_manager import SkillsManager
```
## Design
The manager **never mutates the agent**. It returns prompt text and the caller decides what to do with it, which keeps prompt mutation in one visible place and makes the class testable on its own:
```python theme={null}
# Agent.handle_skills is a single line
self.system_prompt += self.skills.prompt_for_task(task)
```
## Constructor
```python theme={null}
SkillsManager(skills_dir=None, similarity_threshold=0.3)
```
Directory containing skill folders, each holding a `SKILL.md` file with YAML frontmatter. `None` disables skills entirely.
Minimum task/skill similarity for a skill to be selected during dynamic loading.
### Attributes
The configured skills directory.
Metadata for the skills loaded so far.
Read-only. `True` when a directory is configured **and** exists on disk.
## Skill format
Each skill is a folder containing a `SKILL.md` with YAML frontmatter:
```
skills/
├── financial-analysis/
│ └── SKILL.md
└── code-review/
└── SKILL.md
```
```markdown SKILL.md theme={null}
---
name: financial-analysis
description: DCF modeling, ratio analysis, and valuation techniques
---
When performing financial analysis, always start by identifying the
company's revenue drivers, then build a three-statement model...
```
Malformed skills are skipped, never fatal — a file with no frontmatter, unterminated frontmatter, invalid YAML, or one that cannot be read is logged and passed over. A skill with no `name` in its frontmatter falls back to its folder name.
## Methods
### prompt\_for\_task
```python theme={null}
def prompt_for_task(task: Optional[str] = None) -> str
```
Build the skills prompt section. The task argument selects the loading strategy:
When provided, only skills whose description is similar to the task are loaded (dynamic). When `None`, every skill is loaded (static).
Returns the formatted prompt section, or `""` when nothing loaded. Populates `metadata` as a side effect.
```python theme={null}
skills = SkillsManager(skills_dir="./skills")
section = skills.prompt_for_task("Build a DCF valuation model")
# only financial-analysis is selected
```
Uses `DynamicSkillsLoader`, which scores each skill's description against the task by cosine similarity and keeps those above `similarity_threshold`. The loader is built lazily on first use and reused afterwards.
```python theme={null}
section = skills.prompt_for_task(None)
# every skill in the directory is included
```
### load\_metadata
```python theme={null}
def load_metadata(skills_dir: Optional[str] = None) -> List[Dict[str, str]]
```
Tier 1 loading — scan a directory and return one dict per skill with `name`, `description`, `path`, and `content`. Defaults to the configured directory. Returns `[]` when the directory is missing. Entries are returned in sorted order for determinism.
`load_metadata()` **returns** metadata without assigning it to `self.metadata`. Only `prompt_for_task()` populates that attribute — and `load_full_skill()` reads from it. Calling `load_metadata()` alone and then `load_full_skill()` will always return `None`.
### build\_prompt
```python theme={null}
def build_prompt(skills: List[Dict[str, str]]) -> str
```
Render skill metadata as a prompt section. Returns `""` for an empty list. The `# Available Skills` header is emitted exactly once, followed by each skill's name, description, and body.
### load\_full\_skill
```python theme={null}
def load_full_skill(skill_name: str) -> Optional[str]
```
Tier 2 loading — the complete markdown below the frontmatter for one skill, found by name in `metadata`. Returns `None` when the skill is unknown or the file has since become unreadable.
### set\_skills\_dir
```python theme={null}
def set_skills_dir(skills_dir: Optional[str]) -> None
```
Point the manager at a different directory, discarding cached `metadata` and the dynamic loader.
## Agent integration
| `Agent` member | Behavior |
| --------------------------------------------- | ---------------------------------------------------------- |
| `agent.skills` | The `SkillsManager` instance |
| `agent.skills_dir` | Property reading through to `skills.skills_dir` (settable) |
| `agent.skills_metadata` | Property reading through to `skills.metadata` (settable) |
| `agent.handle_skills(task=None)` | Appends `prompt_for_task(task)` to the system prompt |
| `agent.load_skills_metadata(skills_dir=None)` | Delegates to `load_metadata()` |
| `agent.load_full_skill(name)` | Delegates to `load_full_skill()` |
Skills load at `run()` time, not construction, so an agent's recorded system prompt at init does not yet include them.
## Standalone use
```python theme={null}
from swarms.agents.skills_manager import SkillsManager
skills = SkillsManager(skills_dir="./skills")
print(skills.enabled) # True
print([s["name"] for s in skills.load_metadata()])
print(skills.prompt_for_task("review this Python code"))
print(skills.load_full_skill("code-review"))
```
## Related
Guide to authoring and using skills
The class that owns the manager