AI agent skills

These Claude AI agent skills cover the full lifecycle of end-user help documentation: cataloging source knowledge; generating articles and release notes; reviewing them for style, terminology, and AI readiness; facilitating human-in-the-loop reviews; and publishing through Paligo XML CCMS and Zendesk. The skills ship together as a versioned Claude Code plugin with custom MCP servers. All operate at low costs.

Content development plugin​

Search, classify, and ingest knowledge​

Source Librarian​

source-librarian

What it is​

/source-librarian is a low-cost skill that takes in Zendesk tickets, Jira issues, GitHub code, Confluence pages, Notion pages, transcripts, Slack threads, Google Docs, Google Slides, PDFs, plain text, and other sources of product knowledge so drafting skills can find material relevant to the topic they've been given to write about.

How it works​

For each new file, it reads the full content, strips boilerplate, applies tags from a 16-dimension product taxonomy, and writes a PII-free summary and drafting guidance into the file's YAML front matter. A compact master index and one index shard per workflow connects the dots between sources.

The classification process includes:

• A faceted taxonomy with 16 categories and about 400 terms, covering product areas, features, workflows, objects, user roles, lifecycle stages, compliance, issues, and technical components.
• Rules for required tags, so every source was findable by product area, workflow, and purpose, and troubleshooting and integration sources carried the detail they needed.

For support tickets specifically: instead of treating tickets as troubleshooting-only material, the skill surfaces how-to steps, warnings, best practices, and conceptual explanations that would otherwise stay buried in support conversations. Because tickets are high volume, a Python script extracts the content so the company isn't paying for tokens to do it.

Why I built it​

It's expensive for a drafting skill to find and read up to hundreds of files on every run. I needed a way to ingest each piece of content one time only, classify it, and index it so drafting runs know exactly where to find the information they need and read only the information they need.

Generate content​

Diátaxis Drafter​

diataxis-drafter

What it is​

/diataxis-drafter generates customer-facing Help Center articles in any Diátaxis type (how-to guide, tutorial, concept, troubleshooting, or reference).

How it works​

I give the skill a topic and Diátaxis type. The skill reads files catalogued by /source-librarian three cost-saving tiers: index files first, then metadata headers only, and finally full reads of just the files I confirm are relevant. Rules prioritize content sources to read first and most carefully. Flags are thrown for unknowns and contradictions for human review.

The skill also includes Diátaxis templates in a reference file so every article type has a predictable structure.

Why I built it​

I wanted to cheaply generate first drafts of articles to speed up the authoring process, including manually reading through multiple sources of product knowledge myself. I also wanted a way to pull directly from product code things like error messages, UI labels, and user paths.

Example prompts​

• Draft a how-to guide and a troubleshooting article on Feature X.
• Write a concept article about Feature Y.
• Draft an FAQ about the top 10 most common issues in support tickets about Feature Z.

Release Notes Drafter​

release-notes-drafter

What it is​

/release-notes-drafter drafts customer-facing release notes for a specified audience by looking at Github Releases, commits, and Jira tickets. It frames each note in the context of value added to users.

How it works​

The skill creates one note per Jira ticket associated with a release after filtering out internal work such as CI/CD changes, refactors, monitoring, and dependency upgrades, grouping changes that apply only to certain audiences. The final output lists every dropped item with a reason, so reviewers can check the call.

Notes are written to highlight value to users. For example:

It also adjusts tone and formatting for each audience and replaces internal jargon with customer-facing terms.

Why I built it​

I wanted to produce release notes that were more than just changelogs that describe what was built. I wanted to communicate clearly to customers the why behind and changes and how it improves their product experience. I also wanted practical help with grouping notes by product and audience.

Optimize and review​

AI Optimizer​

ai-optimizer

What it is​

/ai-optimizer checks a drafted Help Center article against 25 research-backed criteria for how well AI agents can use it and whether they retrieve it through RAG, web fetch, or MCP tool calling. It returns a report ranked by priority (critical, high, and medium), with a readiness rating for each access pattern.

How it works​

The skill flags things like sections that can't stand on their own, acronyms that aren't defined in each section, inconsistent terms for the same thing, unclear pronouns, reworded error messages, screenshots without text equivalents, content hidden in tabs or accordions, generic headings, missing checkpoints, and missing failure modes. Every recommendation names the exact section and includes replacement text I can use as is.

Why I built it​

I wanted generated content to be easily consumed by the company's internal Claude instance and be structured well for use in Zendesk, including optimized search results.

Vocabulary Pal​

vocabulary-pal

What it is​

/vocabulary-pal audits a Google Doc, Markdown file, text file, or Word document against an organization's custom controlled vocabulary. It flags every non-preferred term and gives the preferred term, the style guide's reasoning, and a suggested rewrite.

How it works​

The skill handles details a simple find-and-replace can't: case-sensitive terms, hyphenation, acronyms that must be spelled out on first use, plurals and possessives, exceptions for terms shown literally in the product UI, and look-alike terms that mean different things. When the context is ambiguous, it flags both readings instead of picking one silently.

Why I built it​

Source materials I generated content from used all kinds of variations of terms, including their spelling and capitalization (for example, common internal use for web app was WebApp, which was not a product name). I wanted to easily catch and fix inconsistencies without manually reading through the text from start to finish or running inadequate manual searches and replaces. I created it as a separate skill so I can run it on any piece of content I write, not just content generated by an AI agent skill in my plugin.

Style Pal​

style-pal

What it is​

/style-pal is an audit skill that checks a document against my company Technical Style Guide, with the Microsoft Style Guide as a fallback. It returns a numbered list of violations with a suggested fix for each.

How it works​

The skill checks for ampersands, title case and gerunds in headings, missing serial commas, click on instead of click, quotation marks used for emphasis, split infinitives, third-person instructions, unbolded UI elements and file names, passive voice, and more. Because the report is numbered, I can reply fix 1, 3, 5 or fix all but 2 and 4 so I stay in control of every change.

Why I built it​

I wanted to easily catch and fix inconsistencies without manually reading through the text from start to finish or running inadequate manual searches and replaces. I created it as a separate skill so I can run it on any piece of content I write, not just content generated by an AI agent skill in my plugin.

Publish output​

Paligo Pal​

paligo-pal

What it is​

/paligo-pal performs actions in the Paligo XML CCMS around documents, folders, forks, images, productions, imports, translation exports and imports, taxonomies, variables, users, and assignments. It also includes a Google Doc to Paligo pipeline that converts a doc into valid DocBook 5.1 XML, uploads its images, and turns Help Center links into Paligo cross-references.

How it works​

A custom Python MCP server connects Claude to the Paligo REST API so the skill can perform actions with natural language prompts. When interacting with documents, the skill applies Paligo's structural rules automatically. It respects section limits (converting extra headings to styled paragraphs), tells procedures apart from ordinary lists, and handles admonitions, tables, and image placement. Safety rules make it fetch the latest XML just before every update, so it never overwrites edits made in the Paligo editor. It also never guesses a document title or folder location.

Why I built it​

Managing and updating content in the Paligo UI requires a lot of clicks, especially for things like changing content across multiple files or managing images. Also, I had a use case for copying drafts from Google Docs into Paligo, which is slow and error prone when done by hand.

Example prompts​

• Convert this Google Doc to Paligo XML and post to a new document in the Product A Guide.
• Remove the Overview article from the Product B Guide by deleting the document and removing it from the table of contents.
• Upload image.png to the media directory and add it at the top of the Prerequisites article in the Product C Guide.

Zendesk Guide Pal​

zendesk-guide-pal

What it is​

/zendesk-guide-pal performs Zendesk Help Center operations, like managing article metadata, content tags, labels, redirect rules, and themes.

How it works​

A custom Python MCP server is a wrapper around the Zendesk Help Center API, including both content management and theming. The skill then accepts natural language prompts for actions like (among many others):

• Add or remove labels by name, on one article or many at once
• See how often each label is used, including labels that no article uses
• Create, update, or delete an article
• List all articles, or only the articles in one category or section
• Find all articles that have a given content tag, with each article's title, URL, section and category
• List all sections, or only the sections in one category
• Create a redirect from one article to another, using article IDs instead of full URLs, with a choice of redirect status (such as 301 or 302)
• Package a local theme folder into a zip that's ready to upload, leaving out hidden files and old zips
• Perform actions in dev or prod

Why I built it​

Performing actions through the Zendesk UI requires lots of repetitive clicking to get things done. This is especially true for custom themes managed locally. I wanted to save time and clicks so I could work faster, more efficiently, and without mistakes.

Example prompts​

• Apply an "export_data" label to every article in the "Export data" section of the Data User Guide.
• Remove callouts with "Coming soon" at the top of all articles with a "sprint_201_release" label.
• List all articles that have no label, including their title and direct URL, and suggest labels.
• List all unused labels and delete them with my approval.

For ultimate time savings, I used my Zendesk Guide MCP server in tandem with my Paligo MCP server to perform multi-system actions, like:

• Publish the updated "Data User Guide" in Paligo to Zendesk and apply the Zendesk label "extract_data" to all new articles created in that guide in Paligo last week.