Code Overview To Confluence logo

Code Overview To Confluence

Organization
testdouble
code-overview-to-confluence

Produces a progressive-disclosure overview of unfamiliar code or a pull request's changes with code-overview and publishes the resulting overview to a user-specified Confluence location. Use when the user wants code or a PR explained, oriented, or made sense of AND the overview posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not produce the overview to a local file only — use code-overview. Does not publish an arbitrary existing markdown file — use markdown-to-confluence. Does not document an already-understood feature to Confluence — use project-documentation-to-confluence. Does not root-cause a bug to Confluence — use investigate-to-confluence. Does not plan or specify a new feature to Confluence — use plan-a-feature-to-confluence. Does not publish to Jira — use work-items-to-jira.

Overview

Publishertestdouble
Repositoryhan
Skill namecode-overview-to-confluence
Stars
320
Forks
26
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by testdouble on GitHub. Read the source before you install it.

Installation

Install the Code Overview To Confluence AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/testdouble/han/tree/main/han-atlassian/skills/code-overview-to-confluence
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/testdouble/han.git /tmp/han
mkdir -p .claude/skills
cp -r /tmp/han/han-atlassian/skills/code-overview-to-confluence .claude/skills/code-overview-to-confluence
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Overview To Confluence in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Overview To Confluence on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Overview To Confluence is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Project Context

  • personal config directory: !bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh" 2>/dev/null || echo "$HOME/.claude"
  • project .han/config.md: !cat .han/config.md 2>/dev/null || echo ""

As your first action, use the Read tool on .han/config.md inside the personal config directory path above. A read that returns no file is no personal configuration: continue silently. When that file or the project .han/config.md probe supplies content, apply it per config-rule.md, which governs precedence between the two files, relative-path resolution, and what to do with a file that reads but cannot be used.

Code Overview to Confluence

This skill runs a progressive-disclosure code overview with the core han-coding:code-overview skill, lets the user review the resulting overview, and then publishes it to a Confluence location that the user must specify. It is a thin orchestrator: the overview work belongs to han-coding:code-overview, and the publishing work belongs to han-atlassian:markdown-to-confluence. This skill only validates its inputs, runs the overview to a scratch file, gets the user's review and publish choice, and hands the file to the publisher.

han-coding:code-overview produces a single scratch file (the overview: what the code does, how it flows, where to start, and — in PR mode — what changed and what to watch when reviewing). It does not produce companion artifacts, so this skill publishes that one file as a single Confluence page — the single-page sibling of han-atlassian:investigate-to-confluence and han-atlassian:project-documentation-to-confluence, not the parent-plus-children tree of han-atlassian:plan-a-feature-to-confluence.

The five steps below are the whole skill. It does not resolve Confluence pages or call the Confluence MCP create/update tools itself; han-atlassian:markdown-to-confluence owns all of that.

Step 1: Validate Inputs

Confirm the skill has everything it needs before spending effort on an overview:

  1. Atlassian MCP reachable (hard requirement). Call mcp__claude_ai_Atlassian__getAccessibleAtlassianResources to confirm the server is connected and retrieve the cloud ID(s). If the tool is not available, the call errors, or it returns no accessible resources (typically an authentication or configuration problem), stop immediately. Tell the user this skill requires the Atlassian MCP server to be installed, configured, and authenticated, and that they can re-run it once it is connected. Do not fall back to a local-only run; for a local-only overview, point them at han-coding:code-overview. This preflight runs first so a missing server fails before any overview work begins.
  2. A target to overview (optional). The target may be a file, directory, symbol, or pull request reference, and an optional size (small, medium, or large). All of this — together with the relevant conversation context — is forwarded to han-coding:code-overview verbatim in Step 2. A target is not required: with none given, han-coding:code-overview defaults to the current branch's changes. Do not resolve or classify the target here; that is han-coding:code-overview's job.
  3. A Confluence destination. Confirm the request provides a target location: a Confluence page URL (to update that page, or create a child under it), or a space (key or name) plus an optional parent page. If none was provided, ask for one with AskUserQuestion, explaining plainly that the skill needs an exact destination because it does not search Confluence. Do not resolve the page tree here — only confirm a location was given. Carry it through to Step 5; han-atlassian:markdown-to-confluence resolves it.

Step 2: Produce the Overview to a Scratch File

Invoke the han-coding:code-overview skill with the Skill tool, forwarding all provided context verbatim: the target (file, directory, symbol, or PR reference, or none for the current branch's changes), any size the user gave, and the relevant conversation context. Do not summarize, trim, or reinterpret the user's context; pass it through so han-coding:code-overview runs exactly as it would on its own (target resolution, mode and size selection, parallel han-core:codebase-explorer exploration, synthesis, and the readability-review pass).

han-coding:code-overview already writes its overview to a scratch file outside the repository and changes no code — except add one explicit instruction: it must write the overview to an explicit scratch path this skill names (for example ${TMPDIR:-/tmp}/code-overview-<slug>.md). Passing the path explicitly keeps the file where this skill expects it even when either .han/config.md configures an output directory, because explicit input outranks the config (see ../../references/config-rule.md). Capture the exact scratch-file path it wrote. That markdown file is the source content for Confluence. Proceed to Step 3 once it finishes.

Step 3: Show the File for Review

Tell the user the exact scratch-file path of the generated overview so they can open and review it before deciding whether to publish. State plainly that the content has not been published anywhere yet, and that no code was changed.

Step 4: Confirm the Publish Choice

Publishing to Confluence puts the content where other people can see it, so require an explicit choice before posting. Ask with AskUserQuestion, restating the scratch-file path and the Confluence destination the user provided. Offer three options, listing the draft option first as the recommended default:

  • "Yes, save it as a draft to edit later (recommended)" — published as an unpublished Confluence draft for the user to review, edit, and publish themselves. This is the default. (Publish mode: draft.)
  • "Yes, publish it live now" — the page goes live immediately. (Publish mode: live.)
  • "No, keep it local only" — nothing is published.

If the user keeps it local only, stop. Report the scratch-file path and state clearly that nothing was published to Confluence. Otherwise, record the chosen publish mode (draft or live) for Step 5.

Step 5: Publish with markdown-to-confluence

Invoke the han-atlassian:markdown-to-confluence skill with the Skill tool, forwarding:

  • the scratch-file markdown path captured in Step 2,
  • the Confluence destination the user provided in Step 1 (the page URL, or the space plus optional parent page), passed through verbatim, and
  • the publish mode the user chose in Step 4 (draft or live), stated explicitly so han-atlassian:markdown-to-confluence does not re-ask.

han-atlassian:markdown-to-confluence resolves the location, reads the file, creates or updates the page in the chosen mode, handles Mermaid diagrams, and reports the resulting page URL. Relay its result to the user: the created or updated page's URL and whether it went live or was saved as a draft. If publishing fails, report the error and confirm the scratch-file markdown is unchanged and intact.

Verification

  1. Inputs validated: the Atlassian server was reachable and a Confluence location was provided — or the skill stopped before doing any work.
  2. Overview produced to a scratch file: han-coding:code-overview ran with the full forwarded context, wrote the overview to a scratch file whose path was captured, and changed no code.
  3. User reviewed: the scratch-file path was shown to the user before any publish.
  4. Explicit choice obtained: the user chose draft, live, or local-only.
  5. Publish delegated and reported: when the user chose to publish, han-atlassian:markdown-to-confluence created or updated the page in the chosen mode and its URL was relayed; when the user declined, only the scratch file exists.

Frequently asked questions

What does the Code Overview To Confluence AI skill do?

Produces a progressive-disclosure overview of unfamiliar code or a pull request's changes with code-overview and publishes the resulting overview to a user-specified Confluence location. Use when the user wants code or a PR explained, oriented, or made sense of AND the overview posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not produce the overview to a local file only — use code-overview. Does not publish an arbitrary existing markdown file — use markdown-to-confluence. Does not document an already-understood feature to Confluence — use project-docum...

Why use Code Overview To Confluence on TypingMind?

Because you install it once and use it with any model. Code Overview To Confluence is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Overview To Confluence in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/testdouble/han/tree/main/han-atlassian/skills/code-overview-to-confluence. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Code Overview To Confluence?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Overview To Confluence?

As many as you like. As long as a model supports skills, you can use Code Overview To Confluence with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Overview To Confluence AI skill free?

Yes. It is published on GitHub by testdouble under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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