And a curated set used by hundreds of engineers at Fin
Skills are a big part of our 2x journey; they allow us to build specialized capabilities for common tasks. We share these skills across our organization via a private, auto-updating plugin marketplace, created by our dedicated team (“team-2x”). When someone builds a skill to do a task in the best way possible, everyone on the team immediately benefits.
Our mission is to break down all technical work into repeatable, high-quality skills that can be run by Agents to augment our engineering work. Every improvement durably compounds into Agents getting things right in our environment, every time. A classic platform play.
As Darragh wrote in 2× – nine months later, within its first three months, our Claude Code plugins repo had become the most actively contributed-to project at Fin with 153 contributors (31% of R&D) and 267 skills.
After all this shipping, here’s what I’ve noticed separates the best skills from the worst.
Good skills:
Do one thing really well.
Are created using a high-quality feedback loop.
Use scripts for the deterministic parts. Have evals that are regularly used and maintained.
Use progressive discovery to avoid bloating context. Have guardrails. Best-effort attempts by Agents that go off-script often result in bad outcomes.
Are cleaned up after iteration. It’s really common for skills to accumulate cruft over time, such as references to an old way of doing something – this information is usually irrelevant.
Are regularly refreshed with new learnings. The skill itself can be instructed to do this, or periodic analysis of session data can achieve this.
Use reference tables and prior learnings – not everything needs to be worked out from first principles every time.
Use hooks to force skill-use when essential – for example, we never want Agents to query Snowflake without having loaded the domain-specific knowledge required to get queries right the first time.
Use the correct plugin. Not everybody needs to use every skill, and plugins help get the right skills to the right Agents at the right time.
Have owners.
Are devoid of changelogs or references to the old ways of doing things.
Are unopinionated. In the vast majority of cases, skills should not assume that specific tools or capabilities are available, beyond what is commonly used.
Are Buzz compatible! (Buzz is our internal remote agent platform.)
Bad skills:
Get the same things wrong every time.
Have nobody looking at output.
…or have non-experts evaluating output.
Aren’t actually used.
Are too large for Claude to actually read in one go.
Can’t easily be invoked by keywords, etc.
Half-ass the work – create a dashboard for humans to make decisions rather than fully delegating the work to the Agent.
If you’re interested in pointing your Agent at a small, edited, curated set of Claude Code skills/hooks that are heavily used by hundreds of engineers at Fin, we just published some. Serious use of these will need customization for your environment.
They include:
skill-tools— Tools for authoring and reviewing Claude Code skills. Includes theskill-reviewskill, which reviews skills against a closed 7-category quality rubric (Structural Discipline, Integrity, Test Coverage, Security, Content Quality, Convention, Cost) with structured JSON output and a determinism contract.security-tools— Harden GitHub Actions workflows against supply-chain and injection attacks. Includes thesecure-github-actionsskill (a 14-rule review checklist plus audit commands) and a hook that auto-loads it when you edit a workflow file.claude-code-tools— Meta-tools for running Claude Code well.permissions-analyzervets your permission allowlist against a GREEN/YELLOW/RED safety model;tool-missesfinds and fixes missing CLI tools / BSD-GNU incompatibilities;cc-cost-analysisis a framework for analyzing Claude Code usage costs from OpenTelemetry data.test-tools— Investigate and fix flaky tests. Thefix-flaky-testsskill detects your framework and CI provider, classifies the flake, and enforces green-CI-as-the-only-verification discipline across RSpec, Jest, pytest, Go test, and more.code-review-tools— Thethermo-nuclear-code-reviewskill runs an extremely strict structural and architectural review, hunting for “code judo” simplifications rather than correctness bugs or style nits. Inspired by Cursor’s plugin of the same name.pr-tools— Open well-formed GitHub pull requests from Claude Code and attach screenshots and recordings to them. Includescreate-pr(intent-gathering, diff validation, public-repo safeguards) andattach-github-assets(upload local images/recordings to GitHub for use in PR and issue markdown).