The Skill Creator’s Checklist: 12 Things to Verify Before Publishing

Publishing an agent skill is easy. Publishing one that people actually trust is harder.

This article is for skill authors, marketplace reviewers, and engineering teams building internal skill catalogs. If you want a practical skill publishing checklist you can run before release, start here. The short version is simple: the best skills are specific, testable, scoped correctly, and honest about where they fail.

Why a pre-publish checklist matters

Thariq’s March 2026 write-up on how the Claude Code team uses skills made one point very clear: it is easy to create bad or redundant skills. That warning matters even more in public marketplaces. A weak skill wastes reviewer time, misfires on user prompts, and teaches teams to distrust the whole catalog.

On a growing marketplace, quality control is not a nice-to-have. It is the thing that separates a useful library from a pile of unmaintained prompts. Anthropic’s official skills documentation, the AgentSkills.io standard, and real marketplace usage patterns all point in the same direction: the best skills are narrow enough to activate cleanly, rich enough to guide judgment, and grounded in real failure cases.

That is why a lightweight agent skill review process works so well. Instead of guessing whether a skill feels good, you verify a small set of concrete signals before it goes live.

The 12-point skill publishing checklist

Use this section as a copyable review template. If a skill cannot pass most of these checks, it is usually not ready to publish.

1. The description tells the model when to activate the skill

The description field in SKILL.md is not marketing copy. It is routing logic for the model. A good description includes trigger phrases, error states, and exclusions. A weak one sounds polished but gives the model nothing concrete to match against.

description: >
  Use when reviewing a skill before publication, checking for overlap,
  weak trigger descriptions, missing gotchas, poor file structure, or
  untested instructions. Triggers on: "review this skill", "is this
  ready to publish", "check my SKILL.md", "audit this agent skill".
  NOT for: writing a new skill from scratch.

If a reviewer cannot answer “what exact user requests should activate this?” in under 30 seconds, revise the description.

2. The skill solves one clear job

Scope creep is one of the fastest ways to make a skill unreliable. A publishable skill should solve one primary job well. It can support adjacent tasks, but it should not quietly expand into deployment, observability, documentation, and code review all at once.

A simple test helps here: could you explain the skill in one sentence without using the word “and” twice? If not, the scope is probably too broad.

3. The gotchas section contains real failure points

Thariq called the gotchas section the highest-signal part of a skill, and that holds up in practice. Marketplace-ready skills almost always include at least 3 to 7 concrete failure cases pulled from real use. Generic warnings like “handle errors carefully” do not count.

Good gotchas entries are specific, corrective, and local to the task:

• What failure happens
• How the agent usually gets it wrong
• What to do instead

If the gotchas section is empty, the skill has probably not been tested enough.

4. The file structure uses progressive disclosure

A good SKILL.md checklist should always ask whether the main file is doing too much. Core instructions belong in SKILL.md. Heavy references, examples, and helper scripts belong in separate files so the agent can pull them only when needed.

my-skill/
├── SKILL.md
├── config.json
├── references/
│   ├── review-rubric.md
│   └── edge-cases.md
├── scripts/
│   └── validate.js
└── examples/
    └── passing-skill.md

As a practical rule, once your main instructions cross roughly 400 to 500 lines, it is worth asking what should move into references/ or examples/.

5. Setup is explicit and portable

Publishing a skill that only works on the creator’s laptop is not a release, it is a private note. Review the setup section for hardcoded usernames, local paths, team-only URLs, and hidden environment assumptions.

A portable skill should document:

• Required environment variables
• Expected tools or CLIs
• Default config values
• What to do if setup is missing

For example, if a helper script needs Node.js 20 or Python 3.12, say so plainly. If the skill reads from a config file, show the expected schema.

6. The skill does not repeat generic model knowledge

This is where many drafts start sounding like filler. The model already knows that tests are good, linting matters, and APIs can fail. Your skill should focus on the facts a general model is least likely to infer correctly: internal naming rules, local deployment hazards, vendor quirks, or exact review criteria.

A useful internal question is: “Would this still help if the model were already very competent?” If the answer is no, cut it.

7. Scripts are used where determinism matters

If part of the workflow needs to behave the same way every time, move it into a script. This matters for validation, formatting, migrations, and anything safety-sensitive. Natural language is good for judgment. Scripts are better for repeatable execution.

#!/usr/bin/env bash
set -euo pipefail
npm run lint
npm test
node scripts/check-frontmatter.js

A review-ready skill should make it clear when to run a script, what the expected output looks like, and when the agent should stop and ask for help.

8. Overlap with existing skills has been checked

Before publishing, compare the proposed skill against existing catalog entries. On ASE, this step matters because duplicate skills fragment trust. Two weakly differentiated “review my code” skills are worse than one excellent one with a clear scope.

Check for overlap in three places:

1. Title and slug similarity
2. Description and trigger overlap
3. Same job, different wording

If the skill overlaps with an existing entry by more than about 70%, the better move is often to improve the existing one or narrow the new one.

9. Internal references and external sources are present

For a public educational skill, include links that help the user verify claims and go deeper. For ASE content, that often means linking to related skill pages, the ASE blog, the Claude Code skills docs, and the AgentSkills.io standard.

Citations do two things. They make the skill easier to audit, and they tell reviewers the author did more than improvise from memory.

10. The examples match real tasks

Examples should look like requests a user would actually make. If the example prompts sound synthetic, the skill probably has not been exercised enough. Include a mix of short triggers and messy real-world prompts.

• review this skill before I submit it to ASE
• check whether this SKILL.md is too broad
• why is my skill not activating for users asking about deploy previews?

This is also the easiest way to catch routing mistakes before publication.

11. There is proof of testing, not just confidence

A real skill quality assurance pass should record what was tested, what failed, and what changed. You do not need a 20-page report. You do need evidence that the author ran the skill against actual prompts and corrected at least a few issues.

A strong testing note includes 5 pieces of information:

• Test date
• Environment or agent
• Sample prompts used
• Observed failures
• Fixes made before publish

If none of that exists, you are publishing optimism, not a reliable tool.

12. The final review asks whether the skill is worth publishing at all

This is the hardest check, but it saves the most time. Not every decent draft deserves release. Some skills should stay private. Some should become internal team docs. Some are better merged into another skill. A healthy marketplace says no often enough to keep the catalog usable.

Before publishing, ask:

• Is this new?
• Is it better than what already exists?
• Will it help a user avoid a costly or repeated mistake?

If the answer is not clearly yes, keep iterating.

A sample review workflow you can reuse

If you want a lightweight process, use this sequence:

1. Read the title, slug, and description first. This catches duplication and routing issues early.
2. Scan the file tree. Check whether SKILL.md is overloaded or missing support files.
3. Read the gotchas section in full. If it is vague, stop there and request revision.
4. Run 3 to 5 realistic prompts. Log activation behavior and obvious failures.
5. Verify setup portability. Remove creator-specific assumptions.
6. Decide publish, revise, or reject. Keep the bar visible.

That review process is short enough for day-to-day use, but strict enough to catch the common marketplace failures we keep seeing.

If you are building your own skills, the related ASE posts on gotchas sections and progressive disclosure pair well with this checklist.

Frequently asked questions

How long should a pre-publish skill review take?

For a small skill, a solid pre-publish review usually takes 15 to 30 minutes. Larger skills with scripts, references, and setup requirements may take 45 minutes or more. If you are skipping review because it feels slow, the skill is probably too broad.

What is the biggest reason agent skills fail after launch?

The most common failure is poor routing. The skill either does not activate when it should, or activates for the wrong requests. After that, vague gotchas and hidden setup assumptions are the next biggest problems.

Should every skill include scripts and a config file?

No. Small skills do not need extra files just to look sophisticated. Add scripts when determinism matters, and add config when values need to vary across users or environments. The goal is clarity, not ceremony.

Conclusion

A strong skill publishing checklist is really a quality filter. It helps you catch the same predictable problems before they reach users: weak descriptions, fuzzy scope, missing gotchas, overloaded files, duplicate ideas, and untested claims.

If you publish skills on a marketplace, that discipline compounds. Each good release makes the catalog more trusted. Each weak one does the opposite.

Use the 12 checks above before your next release, then tighten the process based on what actually fails in review. If you are browsing for proven patterns, explore the catalog on AgentSkillExchange and keep an eye on the editorial archive for more practical guides.