Skills - Orq.ai Documentation

Skills are reusable, instruction-driven capabilities that tell an Agent how to perform a specific task reliably, using the right context, tools, steps, and output format. Attach a Skill to an Agent so it can invoke it on demand when relevant, or reference it statically inside agent instructions, Prompts, and Jinja templates using {{skill.key}}. Any update to a Skill propagates automatically to every reference.

Use Cases

Modular agent capabilities

Build agents that invoke specialized Skills on demand: a support agent that draws on a “summarize thread” Skill only when the conversation warrants it, or a research agent that invokes a “extract key claims” Skill selectively.

Shared tone and brand voice

Package your brand guidelines, writing style, or response format rules into a Skill and embed it across every agent and prompt that needs it. Update once and the change propagates everywhere.

Reusable domain expertise

Encode compliance rules, classification criteria, or structured output schemas as Skills. Any team building on top of the same agents or prompts shares the same versioned definition without duplication.

Using Skills with Agents

Open the Skills section in the agent configuration, click Skills, and search for the Skill to attach it. Once attached, the agent can invoke it when relevant, without the Skill being present in the instructions at all times. Use this for capabilities the agent should draw on selectively depending on the conversation, for example a “summarize thread” Skill invoked only when the user asks for a summary.

Agent configuration panel with a Skill attached for on-demand invocation.

Any update to a Skill propagates automatically to every agent that has it attached.

Creating a Skill

AI Studio
API & SDK
MCP

Choose a Project and Folder, select the button, and choose Skill.Fill in a key that will be used to reference the Skill and configure the content.

curl -X POST https://api.orq.ai/v2/skills \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "display_name": "summarize-thread",
    "description": "Summarizes a support conversation in 3 bullet points",
    "instructions": "Summarize the conversation in exactly 3 bullet points. Be concise.",
    "tags": ["support", "summarization"],
    "path": "Default/Skills"
  }'

from orq_ai_sdk import Orq
import os

orq = Orq(api_key=os.environ["ORQ_API_KEY"])

result = orq.skills.create(
    display_name="summarize-thread",
    description="Summarizes a support conversation in 3 bullet points",
    instructions="Summarize the conversation in exactly 3 bullet points. Be concise.",
    tags=["support", "summarization"],
    path="Default/Skills",
)
print(result.skill.skill_id)

import { Orq } from "@orq-ai/node";

const orq = new Orq({ apiKey: process.env["ORQ_API_KEY"] ?? "" });

const result = await orq.skills.create({
  displayName: "summarize-thread",
  description: "Summarizes a support conversation in 3 bullet points",
  instructions: "Summarize the conversation in exactly 3 bullet points. Be concise.",
  tags: ["support", "summarization"],
  path: "Default/Skills",
});
console.log(result.skill?.skillId);

See the full Create Skill API reference.

Create a skill called "summarize-thread" that summarizes a support conversation in 3 bullet points

The assistant uses create_skill with the display name, instructions, and any tags.

Managing Skills

List

API & SDK
MCP

curl https://api.orq.ai/v2/skills \
  -H "Authorization: Bearer $ORQ_API_KEY"

from orq_ai_sdk import Orq
import os

orq = Orq(api_key=os.environ["ORQ_API_KEY"])

result = orq.skills.list()
for skill in result.data:
    print(skill.skill_id, skill.display_name)

import { Orq } from "@orq-ai/node";

const orq = new Orq({ apiKey: process.env["ORQ_API_KEY"] ?? "" });

const result = await orq.skills.list();
for (const skill of result.data) {
  console.log(skill.skillId, skill.displayName);
}

See the full List Skills API reference.

List all skills in my workspace

The assistant uses list_skills and returns all skills with their keys and descriptions.

Get

API & SDK
MCP

The skill_id parameter accepts either the generated skill ID (e.g. skill_01H...) or the display name.

curl https://api.orq.ai/v2/skills/summarize-thread \
  -H "Authorization: Bearer $ORQ_API_KEY"

from orq_ai_sdk import Orq
import os

orq = Orq(api_key=os.environ["ORQ_API_KEY"])

result = orq.skills.get(skill_id="summarize-thread")
print(result.skill.display_name)

import { Orq } from "@orq-ai/node";

const orq = new Orq({ apiKey: process.env["ORQ_API_KEY"] ?? "" });

const result = await orq.skills.get({ skillId: "summarize-thread" });
console.log(result.skill?.displayName);

See the full Get Skill API reference.

Get the details of skill "summarize-thread"

The assistant uses get_skill with the skill key and returns the full skill configuration.

Update

AI Studio
API & SDK
MCP

Open the Skill in AI Studio, edit the content or settings, and save to publish the update. All references update automatically.

The skill_id parameter accepts either the generated skill ID (e.g. skill_01H...) or the display name.

curl -X PATCH https://api.orq.ai/v2/skills/summarize-thread \
  -H "Authorization: Bearer $ORQ_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "instructions": "Summarize in 3 bullet points. Include a confidence score."
  }'

from orq_ai_sdk import Orq
import os

orq = Orq(api_key=os.environ["ORQ_API_KEY"])

result = orq.skills.update(
    skill_id="summarize-thread",
    instructions="Summarize in 3 bullet points. Include a confidence score.",
)
print(result.skill.skill_id)

import { Orq } from "@orq-ai/node";

const orq = new Orq({ apiKey: process.env["ORQ_API_KEY"] ?? "" });

const result = await orq.skills.update({
  skillId: "summarize-thread",
  updateSkillRequest: {
    instructions: "Summarize in 3 bullet points. Include a confidence score.",
  },
});
console.log(result.skill?.skillId);

See the full Update Skill API reference.

Update skill "summarize-thread" with revised instructions that include a confidence score

The assistant uses update_skill with the skill key and new content.

Delete

AI Studio
API & SDK
MCP

Open the Skill in AI Studio, open the context menu, and select Delete.

The skill_id parameter accepts either the generated skill ID (e.g. skill_01H...) or the display name.

curl -X DELETE https://api.orq.ai/v2/skills/summarize-thread \
  -H "Authorization: Bearer $ORQ_API_KEY"

from orq_ai_sdk import Orq
import os

orq = Orq(api_key=os.environ["ORQ_API_KEY"])

orq.skills.delete(skill_id="summarize-thread")

import { Orq } from "@orq-ai/node";

const orq = new Orq({ apiKey: process.env["ORQ_API_KEY"] ?? "" });

await orq.skills.delete({ skillId: "summarize-thread" });

See the full Delete Skill API reference.

Delete skill "summarize-thread"

The assistant uses delete_skill with the skill key.

Static references with `{{skill.key}}`

Prompt Snippets are now Skills. The {{snippet.key}} syntax is replaced by {{skill.key}}.

Reference a Skill using {{skill.key}}, where key is the key you set when creating the Skill. The Skill content is injected at that position every time it is rendered, and any update to the Skill is automatically reflected in every reference. This works in:

Agent instructions: inject content that should always be present on every run, such as a company policy block or a standard output format. See Agent Studio for more on writing instructions.
Prompts: compose prompts from reusable blocks instead of duplicating text.
Jinja templates: combine {{skill.key}} references with Jinja expressions to compose dynamic, structured prompts from reusable blocks deterministically.

Using a Skill to enrich a configured prompt.

​Use Cases

​Using Skills with Agents

​Creating a Skill

​Managing Skills

​List

​Get

​Update

​Delete

​Static references with {{skill.key}}

Use Cases

Using Skills with Agents

Creating a Skill

Managing Skills

List

Get

Update

Delete

Static references with `{{skill.key}}`