9 posts tagged with "Skills"

A Hermiq agent gets new capabilities through skills: Markdown documents in the open agentskills.io format, stored as OpenRegister objects. In this part you browse the skills catalog, read the anatomy of the seeded example skills, install one onto an agent, and author your own skill twice: once by hand in the markdown form, once in conversation with the seeded skill-creator skill.

Every skill row in the Hermiq catalog carries a badge of seven dots. In this part you learn what the dots mean, run the Qualify action to earn them mechanically, read the scorecard that explains every failure, and attest level 4 as a human curator. You also learn why the ladder deliberately gets harder to climb from level 5 on.

A skill that "feels right" can still add nothing, or make the agent worse. Paired evals answer the question with two runs of the same cases: one with the skill, one without. In this part you use the seeded woo-triage-paired-eval dataset to run a paired baseline against woo-request-triage, read the delta, and watch the L5 evidence appear where Part 2 left a named gap.

A self-improving skill sounds like a skill that edits itself. In Hermiq it is the opposite: every improvement is a draft that must survive a content scan, an eval gate, and your explicit approval before it becomes a new version. In this final part you read the learnings the seeded tender-summary skill has captured, review its pending improvement draft, decide it, and learn the version history, rollback, and republish surfaces that keep the whole loop reversible.

Claude Skills are the mechanism for extending Claude Code with reusable, specialised behaviours. Think of Conduction's own /review-pr, /opsx-new, or the whole hydra-gate-* family: each one is a skill. This first part explains in ten minutes what a skill is, how it gets activated, and when you should not write one. It's part 1 of a four-part track; by the end you'll be ready to write your own in part 2 — and in part 3 we introduce the 7-level maturity framework that takes a skill from "feels good" to "measured good" (part 4 continues with L6 and L7).

In part 1 you saw what a skill is. In this part you'll write one yourself: a working git-status-summary skill that produces a readable summary of the current working tree. At the end it sits in your ~/.claude/skills/ folder, you can invoke it via /git-status-summary, and you'll know how to share it with your team.

You now have a working skill — but does it actually work well? And does it keep working when Claude itself gets upgraded or when you tweak the skill? This third, optional part shows how to evaluate a skill systematically: test scenarios, trigger tests, a baseline measurement, and the eval runner that /skill-creator sets up for you. This is the step from Maturity Level 4 ("feels right") to Level 5 ("measurably right").

In part 3 you took a skill from "feels right" to "measurably right" — Maturity Level 5. For most skills that's enough. But for a handful of skills you use daily, or that steer other skills, you want to go further: a skill that learns from its own executions (L6), and a skill that steers other agents inside a larger workflow (L7). This fourth part shows how you get there — and how the Hydra dashboard lets you monitor your whole skill library for maturity at once.

The previous parts were about what Hydra does. This part is about how: the skills that let the personas do their job. By the end you'll know which skills the automated pipeline (the "Hydra factory") runs and which ones you call yourself as a human, you'll know the five families, and you'll be able to judge when a new skill is worth writing.