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Skill Development Guide -- Build Reusable AI Agent Skills

Skills are Hermes Agent's superpower -- they encode repeatable expertise into reusable, shareable packages. A well-written skill transforms "I need to do X" into a single invocation that handles tool orchestration, error recovery, and output formatting. This skill development guide covers everything from your first SKILL.md to publishing.

Overview

Custom skills capture repeatable workflows -- tool calls, validations, and output formatting -- into a package you, your team, or the community can reuse. Following best practices for skill development ensures your skills are testable, maintainable, and production-ready.

How It Works

The Rule of Three

Before creating a skill, perform the task manually at least three times: 1. First time: Learn what's needed 2. Second time: Refine your approach 3. Third time: Encode the pattern as a skill

SKILL.md Anatomy

---
name: my-skill-name
description: One-sentence purpose
version: 1.0.0
author: your-handle
tags: [tag1, tag2]
required_connectors: [connector-a]
quality_tier: beta
---

Followed by: What This Skill Does, When to Use, Required Setup, Step-by-Step Workflow (with error handling per step), Example Output, Troubleshooting, Changelog.

Trigger Patterns

Write 5-10 trigger patterns covering different ways users might ask. Good: "Check our marketing performance this week" -- specific enough to avoid false positives but broad enough to catch real intent. Bad: "marketing" (too broad) or overly specific variations.

Verification Between Steps

  • Schema verification: Does response have expected shape?
  • Completeness verification: Did you get everything?
  • Freshness verification: Is data current?
  • Business rule verification: Are values in expected ranges?

Error Recovery Patterns

  • Transient errors: Retry with exponential backoff (max 3 attempts, include jitter)
  • Auth errors: Don't retry -- return clear re-auth message
  • Data errors: Return partial results with clear caveats
  • Partial failures: Return successes + failure summary

Testing Methodology

Test Type What to Test
Unit Each step in isolation with mock inputs
Happy path Full end-to-end with known-good data
Edge cases Empty data, maximum data, missing fields, special characters, date boundaries
Error injection Disconnect connector, malformed data, rate limits, invalid params
Regression Re-run full suite after any change; weekly smoke test for production skills

Skill Lifecycle

Draft → Beta (tested by author + 1 other) → Production (2+ weeks stable) → Deprecated (replacement exists, 30-90 day migration) → Archived

Benefits

  • Knowledge transfer: Skills encode institutional knowledge without requiring prompt engineering
  • Error reduction: Consistent validation and error handling applied every time
  • Team scaling: One well-tested skill serves the entire team
  • Community contribution: Share what you build; benefit from others' work

FAQ

When should I create a Hermes Agent skill vs using a prompt?

Create a skill when you've done the task 3+ times manually, it involves multiple tool calls, it needs guardrails (validation, approval gates), or someone else needs to do it. Use prompts for one-off or exploratory tasks.

How do I test a Hermes Agent skill before publishing?

Test each step in isolation with mock data, run the full workflow end-to-end, test edge cases (empty/maximum/malformed data), deliberately inject errors, and re-run the full suite after any change. Schedule weekly smoke tests for production skills.

What makes a good trigger pattern for skills?

Good triggers are specific enough to avoid false positives but broad enough to catch natural variations. Write 5-10 patterns covering different formality levels, time windows, and specificity. Avoid single-word triggers and overly specific patterns.

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