Add Skill

POST

api

skills

Add Skill

curl --request POST \
  --url https://api.example.com/api/v1/skills \
  --header 'Content-Type: application/json' \
  --data '
{
  "data": {},
  "wait": true,
  "timeout": 123
}
'

import requests

url = "https://api.example.com/api/v1/skills"

payload = {
    "data": {},
    "wait": True,
    "timeout": 123
}
headers = {"Content-Type": "application/json"}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({data: {}, wait: true, timeout: 123})
};

fetch('https://api.example.com/api/v1/skills', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/api/v1/skills",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'data' => [
        
    ],
    'wait' => true,
    'timeout' => 123
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/api/v1/skills"

	payload := strings.NewReader("{\n  \"data\": {},\n  \"wait\": true,\n  \"timeout\": 123\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/api/v1/skills")
  .header("Content-Type", "application/json")
  .body("{\n  \"data\": {},\n  \"wait\": true,\n  \"timeout\": 123\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/skills")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"data\": {},\n  \"wait\": true,\n  \"timeout\": 123\n}"

response = http.request(request)
puts response.read_body

{
  "status": "ok",
  "result": {
    "status": "success",
    "uri": "viking://agent/skills/search-web/",
    "name": "search-web",
    "auxiliary_files": 0
  },
  "time": 0.15
}

{
  "status": "ok",
  "result": {
    "status": "success",
    "uri": "viking://agent/skills/code-runner/",
    "name": "code-runner",
    "auxiliary_files": 3
  },
  "time": 0.25
}

Add a skill to the knowledge base. Skills define capabilities that agents can invoke. OpenViking automatically detects and converts MCP tool definitions to skill format.

Skills are vectorized and indexed for semantic retrieval. Use wait=true or call /api/v1/system/wait to ensure processing completes.

Authentication

Requires API key authentication via X-API-Key header.

Request Body

object | string

required

Skill data in one of four supported formats:

Skill format (dict with name, description, content)
MCP Tool format (dict with inputSchema - auto-converted)
String (SKILL.md content with YAML frontmatter)
Path (file or directory path)

boolean

default:"false"

Wait for vectorization to complete before returning

number

default:"null"

Timeout in seconds when wait=true

Skill Data Formats

Format 1: Skill Dict

{
  "name": "search-web",
  "description": "Search the web for current information",
  "content": "# search-web\n\nSearch the web for current information.\n\n## Parameters\n- **query** (string, required): Search query\n- **limit** (integer, optional): Max results, default 10",
  "allowed_tools": ["HttpClient", "JsonParser"],
  "tags": ["web", "search"]
}

Format 2: MCP Tool (Auto-Converted)

{
  "name": "calculator",
  "description": "Perform mathematical calculations",
  "inputSchema": {
    "type": "object",
    "properties": {
      "expression": {
        "type": "string",
        "description": "Mathematical expression to evaluate"
      }
    },
    "required": ["expression"]
  }
}

OpenViking detects MCP format by the presence of inputSchema and automatically converts it to skill format with generated markdown documentation.

Format 3: SKILL.md String

---
name: code-runner
description: Execute code in various languages
allowed-tools:
  - FileSystem
  - ProcessRunner
tags:
  - code
  - execution
---

# code-runner

Execute code in various languages safely.

## Parameters
- **language** (string, required): Programming language
- **code** (string, required): Code to execute
- **timeout** (integer, optional): Timeout in seconds

Format 4: File Path

{
  "data": "./skills/search-web/SKILL.md"
}

Or for directories with auxiliary files:

{
  "data": "./skills/code-runner/"
}

Response

string

Response status (ok or error)

object

Skill creation result

Show Result Object

string

Creation status (success)

string

URI where skill was stored (e.g., viking://agent/skills/search-web/)

string

Skill name in kebab-case

number

Number of auxiliary files included (when adding from directory)

number

Request processing time in seconds

Examples

curl -X POST http://localhost:1933/api/v1/skills \
  -H "Content-Type: application/json" \
  -H "X-API-Key: your-key" \
  -d '{
    "data": {
      "name": "search-web",
      "description": "Search the web for current information",
      "content": "# search-web\n\nSearch the web for current information.\n\n## Parameters\n- **query** (string, required): Search query\n- **limit** (integer, optional): Max results, default 10"
    }
  }'

curl -X POST http://localhost:1933/api/v1/skills \
  -H "Content-Type: application/json" \
  -H "X-API-Key: your-key" \
  -d '{
    "data": {
      "name": "calculator",
      "description": "Perform mathematical calculations",
      "inputSchema": {
        "type": "object",
        "properties": {
          "expression": {
            "type": "string",
            "description": "Mathematical expression to evaluate"
          }
        },
        "required": ["expression"]
      }
    }
  }'

# Add from skill dict
skill = {
    "name": "search-web",
    "description": "Search the web for current information",
    "content": """
# search-web

Search the web for current information.

## Parameters
- **query** (string, required): Search query
- **limit** (integer, optional): Max results, default 10
"""
}
result = client.add_skill(skill)
print(f"Added: {result['uri']}")

# Add from MCP tool (auto-converted)
mcp_tool = {
    "name": "calculator",
    "description": "Perform mathematical calculations",
    "inputSchema": {
        "type": "object",
        "properties": {
            "expression": {
                "type": "string",
                "description": "Mathematical expression to evaluate"
            }
        },
        "required": ["expression"]
    }
}
result = client.add_skill(mcp_tool)
print(f"Added: {result['uri']}")

# Add from file
result = client.add_skill("./skills/search-web/SKILL.md")
print(f"Added: {result['uri']}")

# Add from directory (includes auxiliary files)
result = client.add_skill("./skills/code-runner/")
print(f"Added: {result['uri']}")
print(f"Auxiliary files: {result['auxiliary_files']}")

# Add from file
openviking add-skill ./skills/search-web/SKILL.md

# Add from directory and wait for processing
openviking add-skill ./skills/code-runner/ --wait

{
  "status": "ok",
  "result": {
    "status": "success",
    "uri": "viking://agent/skills/search-web/",
    "name": "search-web",
    "auxiliary_files": 0
  },
  "time": 0.15
}

{
  "status": "ok",
  "result": {
    "status": "success",
    "uri": "viking://agent/skills/code-runner/",
    "name": "code-runner",
    "auxiliary_files": 3
  },
  "time": 0.25
}

MCP Tool Conversion

When you provide a dict with inputSchema, OpenViking automatically converts it to skill format: Input (MCP):

{
  "name": "search_web",
  "description": "Search the web",
  "inputSchema": {
    "type": "object",
    "properties": {
      "query": {"type": "string", "description": "Search query"},
      "limit": {"type": "integer", "description": "Max results"}
    },
    "required": ["query"]
  }
}

Output (Skill):

---
name: search-web
description: Search the web
---

# search-web

Search the web

## Parameters

- **query** (string) (required): Search query
- **limit** (integer) (optional): Max results

## Usage

This tool wraps the MCP tool `search-web`. Call this when the user needs functionality matching the description above.

Best Practices

Use Clear Descriptions

# Good - specific and actionable
skill = {
    "name": "search-web",
    "description": "Search the web for current information using Google",
    ...
}

# Less helpful - too vague
skill = {
    "name": "search",
    "description": "Search",
    ...
}

Use Kebab-Case for Names

search-web ✅
searchWeb ❌
search_web ❌

Include Comprehensive Content

Clear parameter descriptions with types
When to use the skill
Concrete examples
Edge cases and limitations

List Skills - View all skills
Search Skills - Semantic search
Remove Skill - Delete a skill
Wait for Processing - Ensure vectorization completes

Add Skill

curl --request POST \
  --url https://api.example.com/api/v1/skills \
  --header 'Content-Type: application/json' \
  --data '
{
  "data": {},
  "wait": true,
  "timeout": 123
}
'

import requests

url = "https://api.example.com/api/v1/skills"

payload = {
    "data": {},
    "wait": True,
    "timeout": 123
}
headers = {"Content-Type": "application/json"}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({data: {}, wait: true, timeout: 123})
};

fetch('https://api.example.com/api/v1/skills', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.example.com/api/v1/skills",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'data' => [
        
    ],
    'wait' => true,
    'timeout' => 123
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/api/v1/skills"

	payload := strings.NewReader("{\n  \"data\": {},\n  \"wait\": true,\n  \"timeout\": 123\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.example.com/api/v1/skills")
  .header("Content-Type", "application/json")
  .body("{\n  \"data\": {},\n  \"wait\": true,\n  \"timeout\": 123\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.example.com/api/v1/skills")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"data\": {},\n  \"wait\": true,\n  \"timeout\": 123\n}"

response = http.request(request)
puts response.read_body

{
  "status": "ok",
  "result": {
    "status": "success",
    "uri": "viking://agent/skills/search-web/",
    "name": "search-web",
    "auxiliary_files": 0
  },
  "time": 0.15
}

{
  "status": "ok",
  "result": {
    "status": "success",
    "uri": "viking://agent/skills/code-runner/",
    "name": "code-runner",
    "auxiliary_files": 3
  },
  "time": 0.25
}

Overview

Resources

Filesystem

Search & Retrieval

Sessions

Skills

System

Admin

Authentication

Request Body

Skill Data Formats

Format 1: Skill Dict

Format 2: MCP Tool (Auto-Converted)

Format 3: SKILL.md String

Format 4: File Path

Response

Examples

MCP Tool Conversion

Best Practices

​Authentication

​Request Body

​Skill Data Formats

​Format 1: Skill Dict

​Format 2: MCP Tool (Auto-Converted)

​Format 3: SKILL.md String

​Format 4: File Path

​Response

​Examples

​MCP Tool Conversion

​Best Practices

​Related Endpoints

Authentication

Request Body

Skill Data Formats

Format 1: Skill Dict

Format 2: MCP Tool (Auto-Converted)

Format 3: SKILL.md String

Format 4: File Path

Response

Examples

MCP Tool Conversion

Best Practices

Related Endpoints