Investigate To Confluence logo

Investigate To Confluence

Organization
testdouble
investigate-to-confluence

Runs an evidence-based investigation of a bug, failure, or unexpected behavior with investigate and publishes the resulting investigation report to a user-specified Confluence location. Use when the user wants something debugged, diagnosed, or root-caused AND the findings posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not investigate to a local file only — use investigate. 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 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 nameinvestigate-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 Investigate 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/investigate-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/investigate-to-confluence .claude/skills/investigate-to-confluence
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Investigate 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 Investigate 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 Investigate 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.

Investigate to Confluence

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

han-coding:investigate produces a single report file (the investigation plan: problem statement, evidence summary, root cause analysis, planned fix, validation results, and summary). 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: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 investigation:

  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 investigation, point them at han-coding:investigate. This preflight runs first so a missing server fails before any investigation work begins.
  2. A symptom or question to investigate. Confirm the request names a bug, failure, error, integration, or unexpected behavior to investigate. This — together with any relevant conversation context — is forwarded to han-coding:investigate verbatim in Step 2. If the request is too thin to start, let han-coding:investigate run its own investigation rather than pre-empting it here.
  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 Investigation Report to a Temporary File

Invoke the han-coding:investigate skill with the Skill tool, forwarding all provided context verbatim: the symptom or question, any known reproduction steps or error messages, any suspected entry points, and the relevant conversation context. Do not summarize, trim, or reinterpret the user's context; pass it through so han-coding:investigate runs exactly as it would on its own (parallel investigators, conditional specialist analysts, adversarial validation, and the final report) — except add two explicit instructions:

  • It must write the resulting investigation report to a file under /tmp/ (for example /tmp/<symptom-slug>.md) rather than into the project's docs or plans directory. This keeps the working report out of the repo until the user decides to publish it, and because the path is explicit input it outranks any output-directory the project or personal .han/config.md supplies (see ../../references/config-rule.md).
  • It must stop after producing the report. han-coding:investigate normally ends by presenting the plan for approval and can trigger the fix's implementation on approval; this skill wants the report only, so instruct it not to implement the fix or change any code — this skill publishes findings, it does not ship them.

Let han-coding:investigate complete its full investigation process. Capture the exact /tmp/ 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 /tmp/ path of the generated investigation report 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 /tmp/ 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 /tmp/ report 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 /tmp/ markdown file 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 /tmp/ markdown file is unchanged and intact.

Verification

  1. Inputs validated: the Atlassian server was reachable, a symptom or question to investigate was present, and a Confluence location was provided — or the skill stopped before doing any work.
  2. Report produced to /tmp: han-coding:investigate ran with the full forwarded context, wrote the investigation report to a /tmp/ file whose path was captured, and did not implement the fix or change any code.
  3. User reviewed: the /tmp/ 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 /tmp/ report exists.

Frequently asked questions

What does the Investigate To Confluence AI skill do?

Runs an evidence-based investigation of a bug, failure, or unexpected behavior with investigate and publishes the resulting investigation report to a user-specified Confluence location. Use when the user wants something debugged, diagnosed, or root-caused AND the findings posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not investigate to a local file only — use investigate. 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-confl...

Why use Investigate To Confluence on TypingMind?

Because you install it once and use it with any model. Investigate 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 Investigate To Confluence in TypingMind?

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

Which AI models can use Investigate 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 Investigate To Confluence?

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

Is the Investigate 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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