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Knot provides a machine-readable API specification at /skill.md that allows AI agents to discover wallet capabilities automatically — without hardcoded API knowledge.

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What is /skill.md?

The /skill.md endpoint serves a markdown file that describes Knot’s full API surface. An AI agent can fetch this file at startup to understand:
  • Available endpoints and what they do
  • Required parameters and their types
  • Authentication methods
  • Response formats and field definitions
  • Error handling guidelines

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Fetching the skill spec

curl https://api.useknot.xyz/skill.md
The response is a markdown file (1,100+ lines) containing:
  • A quick start guide
  • Authentication instructions
  • Full endpoint documentation with request and response examples
  • Error handling guidelines

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How an agent uses skill discovery

1

Fetch on startup

The agent retrieves /skill.md when it initializes, before making any API calls.
2

Parse capabilities

The agent processes the markdown to understand which actions are available and what parameters they require.
3

Construct calls

The agent builds valid API calls based on the specification, using correct endpoints and parameters.
4

Stay updated

When Knot adds new features or endpoints, the agent discovers them automatically on the next startup or refresh.

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Integration example

import requests

def discover_capabilities():
    response = requests.get("https://api.useknot.xyz/skill.md")
    skill_content = response.text

    # Parse the markdown to extract endpoints
    # Use the capabilities to construct API calls

    return skill_content

# Fetch capabilities at startup
capabilities = discover_capabilities()

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Forward compatibility

Using /skill.md for discovery makes your agent forward-compatible with future Knot updates:
Traditional approachskill.md approach
Hardcoded API knowledgeDynamic discovery at runtime
Requires code updates for new featuresAutomatic feature discovery
Version-specific integrationAlways reflects the current API
Manual documentation syncSelf-documenting
If you build a skill-discovery-based agent, you gain new Knot capabilities for free — no code changes required when Knot ships new endpoints.

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Best practices

Fetch at startup

Load skill.md when your agent initializes so it understands available actions before it needs them.

Cache locally

Cache the skill file in memory or on disk to avoid fetching it on every request.

Refresh periodically

Re-fetch skill.md daily or weekly to pick up new endpoints and updated documentation.

Parse systematically

Build a structured parser to extract endpoints, parameters, and examples from the markdown.