Agent skill

Plan A Feature To Confluence

by testdouble in testdouble/han

Builds a feature specification from scratch with plan-a-feature and publishes it to a user-specified Confluence location, posting the spec as a parent page and each companion artifact (decision log…

MITAuto-check passedDevelopment

Install Plan A Feature To Confluence

skills CLI
$ npx skills add testdouble/han --skill plan-a-feature-to-confluence -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install testdouble/han plan-a-feature-to-confluence --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/testdouble/han.git skills-src && mkdir -p .claude/skills && cp -r skills-src/han-atlassian/skills/plan-a-feature-to-confluence .claude/skills/plan-a-feature-to-confluence && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
plan-a-feature-to-confluence
GitHub stars
279
Token cost
~4.2k tokens
SKILL.md length
2,229 words
Files
1
Skills in repo
54
Repo updated
First seen
Licence
MIT

At a glance

Builds a feature specification from scratch with plan-a-feature and publishes it to a user-specified Confluence location, posting the spec as a parent page and each companion artifact (decision log…

  • Works in 6 steps: Validate Inputs → Produce the Plan to a Temporary Folder → Show the Files for Review → …
  • The user wants a new feature planned
  • SKILL.md covers Project Context, Step 1: Validate Inputs, Step 2: Produce the Plan to a… and Step 3: Show the Files for…, plus 3 more sections
  • Calls bash

What it does

Plan A Feature To Confluence is an agent skill from testdouble/han. Builds a feature specification from scratch with plan-a-feature and publishes it to a user-specified Confluence location, posting the spec as a parent page and each companion artifact (decision log, team findings, technical notes) as a child page beneath it. Use when the user wants a new feature planned, designed, scoped, or specified AND posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not plan to local files only — use plan-a-feature. Does not publish an arbitrary existing…

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Architecture decision records and Load testing. It works with Confluence and Model Context Protocol. The repository describes itself as: Han: AI skills and agents for "Solo" product engineers and small teams. The licence is MIT.

When your agent uses it

  • The user wants a new feature planned
  • Specified AND posted to a Confluence space

Example prompts

  • “Use the plan-a-feature-to-confluence skill to build a feature specification from scratch with plan-a-feature and publishes it to a user-specified…”
  • “/plan-a-feature-to-confluence”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit, Glob, Grep, Skill, Bash(find *), mcp__claude_ai_Atlassian__getAccessibleAtlassianResources, Bash(bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh")

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Validate Inputs
  2. Produce the Plan to a Temporary Folder
  3. Show the Files for Review
  4. Confirm the Publish Choice
  5. Rewrite Cross-Links to Title Macros, Then Publish the Tree
  6. Verification

What it can do on your machine

Read from SKILL.md and the folder at commit abba73a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Glob
    • Grep
    • Skill
    • Bash(find *)
    • mcp__claude_ai_Atlassian__getAccessibleAtlassianResources
    • Bash(bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh")

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • bash

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Plan A Feature To Confluence loads about 4.2k tokens when it runs. Until then it costs about 191 tokens; SKILL.md has 2,229 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~191
When it runs · the whole SKILL.md, loaded when a task matches
~4.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from testdouble/han at commit abba73a, republished under its MIT licence (© testdouble). 2,229 words, ~4,156 tokens.

Download SKILL.mdSave it as .claude/skills/plan-a-feature-to-confluence/SKILL.md (or your agent's skills folder).
name
plan-a-feature-to-confluence
description
Builds a feature specification from scratch with plan-a-feature and publishes it to a user-specified Confluence location, posting the spec as a parent page and each companion artifact (decision log, team findings, technical notes) as a child page beneath it. Use when the user wants a new feature planned, designed, scoped, or specified AND posted to a Confluence space or page. Requires a configured Atlassian MCP server. Does not plan to local files only — use plan-a-feature. Does not publish an arbitrary existing markdown file — use markdown-to-confluence. Does not refine or stress-test an existing plan — use iterative-plan-review. Does not document already-built features to Confluence — use project-documentation-to-confluence.
allowed-tools
Read, Write, Edit, Glob, Grep, Skill, Bash(find *), mcp__claude_ai_Atlassian__getAccessibleAtlassianResources, Bash(bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh")
arguments
size
argument-hint
[size: small | medium | large] [feature description] [confluence location: page URL or space + parent] [--mode draft|live (default draft)]

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.

Plan a Feature to Confluence

This skill builds a feature specification with the core han-planning:plan-a-feature skill, lets the user review the result, and then publishes it to a Confluence location that the user must specify. It is a thin orchestrator: the planning work belongs to han-planning:plan-a-feature, and the publishing work belongs to han-atlassian:markdown-to-confluence. This skill only validates its inputs, runs the planning skill to a temporary folder, gets the user's review and publish choice, and hands each file to the publisher.

han-planning:plan-a-feature produces a small set of files — the primary feature-specification.md plus companion artifacts under artifacts/ (the decision log, the team findings, and a lazily-created technical-notes file). This skill publishes the spec as a parent page and each companion artifact as a child page beneath it, so the whole plan lands in Confluence as one small page tree. The files cross-reference each other with relative links that do not resolve once each file is its own Confluence page. Because this skill decides every page's title up front, it rewrites those cross-file links into Confluence title-based page-link macros (the <ac:link><ri:page ri:content-title="..."/>…</ac:link> form; Step 5 gives the exact macro to emit, link body and all) before creating any page — these resolve by title at view time, so no page URL or ID has to exist first. That collapses publishing to a single create pass: there is no separate relink-and-update pass, and each page is created exactly once.

The six 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 producing a plan:

  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 local-only planning, point them at han-planning:plan-a-feature. This preflight runs first so a missing server fails before any planning work begins.
  2. A feature to plan. Confirm the request names a feature, capability, or system behavior to specify. This — together with the size argument and any relevant conversation context — is forwarded to han-planning:plan-a-feature verbatim in Step 2. If the request is too thin to start, let han-planning:plan-a-feature run its own interview; do not pre-empt it here.
  3. A Confluence destination. Confirm the request provides a target location: a Confluence page URL (to update that page, or create the spec as 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 Plan to a Temporary Folder

Invoke the han-planning:plan-a-feature skill with the Skill tool, forwarding all provided context verbatim: the size argument (if the user passed small, medium, or large), the feature description, any known constraints or entry points, and the relevant conversation context. Do not summarize, trim, or reinterpret the user's context; pass it through so han-planning:plan-a-feature runs exactly as it would on its own — interview, review team, finding resolution, and plan-synthesizer synthesis included — except add one explicit instruction: it must write its output folder under /tmp/ (for example /tmp/<feature-slug>/) rather than into the repo's docs directory, and it should not prompt the user to choose or confirm an output location, because this skill owns that decision. This keeps the working plan 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).

Let han-planning:plan-a-feature complete its full process. Capture the exact /tmp/ paths of every file it wrote:

  • /tmp/<feature-slug>/feature-specification.md — the primary spec (always written).
  • /tmp/<feature-slug>/artifacts/decision-log.md — the decision history (always written).
  • /tmp/<feature-slug>/artifacts/team-findings.md — the review-team findings (always written).
  • /tmp/<feature-slug>/artifacts/feature-technical-notes.md — load-bearing mechanics. Lazily created — only present if at least one technical note qualified. Confirm whether it exists before relying on it.

Proceed to Step 3 once it finishes.

Step 3: Show the Files for Review

Tell the user the exact /tmp/ paths of every generated file — the spec and each companion artifact that was actually written (the technical-notes file only if it exists) — so they can open and review them before deciding whether to publish. State plainly that nothing has been published anywhere yet.

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 paths and the Confluence destination the user provided, and making clear that publishing creates one parent page (the spec) plus one child page per companion artifact, and that the cross-page links between them resolve by page title — so the published pages should not be renamed in Confluence afterward, or the inbound cross-links break. Offer three options, listing the draft option first as the recommended default:

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

If the user keeps it local only, stop. Report the /tmp/ folder path and state clearly that nothing was published to Confluence. Otherwise, record the chosen publish mode (draft or live) for Step 5. The chosen mode applies to every page in the tree.

Show full SKILL.md (1,161 more words)Show less

Publishing is a single create pass: rewrite the cross-file links into title-based page-link macros first, then create each page once with its final body. No second update pass is needed, because the macros resolve by title and do not depend on any page URL or ID.

Decide every page's final title up front. The title is used in two places — as the page's create-title, and as the ri:content-title in every macro that links to that page — so pick each title once and reuse it in both, so they can never drift apart:

  • Spec (the parent page): the feature name.
  • Decision log: <Feature Name> — Decision Log.
  • Team findings: <Feature Name> — Team Findings.
  • Technical notes (only if the file exists): <Feature Name> — Technical Notes.

These titles must be distinct within the target space for the macros to resolve unambiguously. A ri:content-title macro resolves against the whole space, not just this tree, so a title that collides with a page that already exists in the destination space is a real hazard: the link can resolve to the wrong page, and the create call may fail or be rejected for a duplicate title. The feature-name prefix keeps the four titles distinct from each other; pick a spec title specific enough that it is unlikely to already exist in the space, and if you have any signal that one does (for example the user pointed at a page that already carries the feature name), choose a more specific title before publishing.

  1. Rewrite cross-file links to title macros, leaving the /tmp/ originals intact. Write the rewritten copies to a dedicated subfolder (for example /tmp/<feature-slug>/.confluence-publish/) so the originals the user reviewed in Step 3 keep their working local markdown links. For each file, read it once and rewrite only the cross-file links:

    • Resolve each relative markdown link target against the directory of the file being rewritten. If it resolves to another file in the published set, replace the whole markdown link [text](target#fragment) with a Confluence title-based page-link macro pointing at that file's pre-decided title:

      <ac:link><ri:page ri:content-title="TARGET PAGE TITLE"/><ac:plain-text-link-body><![CDATA[text]]></ac:plain-text-link-body></ac:link>

      Omit ri:space-key — the whole tree lands in one space, so a same-space title reference resolves without it. Keep the original link text inside the link body. If that text contains the sequence ]]>, it would close the CDATA section early and produce malformed storage XML, so split it across two CDATA sections (]] in the first, > in the next) or drop the CDATA wrapper and XML-escape the text instead. Plain markdown emphasis in the link text (**bold**) is not rendered inside a plain-text link body; it posts as literal characters.

    • Drop the #fragment (the #d4-..., #t3-..., or section anchor). Confluence Cloud generates its own heading anchors with a scheme that does not match these slugs, so the link lands the reader at the top of the correct page, not the exact heading. (The macro form leaves the door open to add an explicit ri:anchor later if a space's heading-anchor scheme is pinned down; do not emit anchors now.)

    • Leave every other link, and all other content, exactly as written. Do not touch links that point outside the published set (external URLs, code references).

  2. Publish the tree in one create pass. Use the Skill tool for every call, and apply the publish mode the user chose in Step 4 to all of them — state it explicitly so han-atlassian:markdown-to-confluence does not re-ask.

    • Publish the spec (the parent page) first, from its rewritten copy. Invoke han-atlassian:markdown-to-confluence, forwarding the rewritten spec copy's path, the Confluence destination the user provided in Step 1 (passed through verbatim), the publish mode from Step 4, and the spec title decided above. Capture the resulting spec page's URL and page ID — the parent for the artifact pages, and needed for the final report.
    • Publish each existing artifact as a child of the spec page, from its rewritten copy. For each artifact file that exists (decision-log.md, team-findings.md, and feature-technical-notes.md only if it was created), invoke han-atlassian:markdown-to-confluence again, forwarding the rewritten artifact copy's path, the spec page's URL as the destination with the intent to create a new child page under it (state this explicitly so the publisher does not ask whether to update the spec page), the same publish mode, and the artifact's pre-decided title. Publish the artifacts one at a time so each create resolves against the same parent.

    han-atlassian:markdown-to-confluence owns location resolution, the create call, and Mermaid handling for each file. Because every body already carries its final title-macro links, each page is created exactly once — there is no update pass.

Mermaid still posts as source. As han-atlassian:markdown-to-confluence reports, Mermaid diagrams publish as fenced code blocks, not rendered diagrams, unless the space has a Mermaid macro. This is not something to silently fix.

Relay the result to the user: the spec parent page's URL, every artifact child page's URL, whether the tree went live or was saved as drafts, and the caveats: cross-page links resolve by page title and land at the top of the target page (heading-level anchors are not preserved); because they resolve by title, renaming a published page in Confluence may break inbound cross-page links; and the Mermaid note. If any create fails partway through the tree, report which file failed and its error, and note which pages were already created. Warn the user that those already-created pages carry title-macro links pointing at the pages that did not get created, so those links dangle until the missing pages exist under their intended titles — and that simply re-running the whole skill would re-create the pages that already succeeded, producing duplicate-title pages that break title resolution for the tree. Recommend they create the missing page(s) by hand under the intended titles, or delete the partial tree and re-publish from clean. Confirm the /tmp/ originals are unchanged and intact either way.

Step 6: Verification

  1. Inputs validated: the Atlassian server was reachable, a feature to plan was present, and a Confluence location was provided — or the skill stopped before doing any work.
  2. Plan produced to /tmp: han-planning:plan-a-feature ran with the full forwarded context and wrote its files under a /tmp/ folder whose paths were captured, including whether the lazily-created technical-notes file exists.
  3. User reviewed: the /tmp/ paths were shown to the user before any publish.
  4. Explicit choice obtained: the user chose draft, live, or local-only.
  5. Tree published in a single pass: when the user chose to publish, titles were decided up front, cross-file links were rewritten into title-based page-link macros in copies under .confluence-publish/ (fragments dropped, /tmp/ originals untouched), the spec was posted as the parent page and each existing companion artifact as a child page in the chosen mode, and each page was created exactly once with its URL captured.
  6. Reported: every page URL was relayed with the publish mode, the resolve-by-title and land-at-page-top caveat, the rename caveat, and the Mermaid note; when the user declined, only the /tmp/ files exist.

© testdouble, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in han-atlassian/skills/plan-a-feature-to-confluence of testdouble/han.

Open the folder on GitHubat commit abba73a

Compare with similar skills

Plan A Feature To Confluence next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Plan A Feature To Confluence compared with similar skills
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Grill With Docsalirezarezvani/claude-skills28k—~1.8kAutomated safety check: PassMIT
Model Domaindanielvm-git/bigpowers257—~1.2kAutomated safety check: PassMIT
Diag Harnessruvnet/metaharness690—~835Automated safety check: PassMIT

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Questions about Plan A Feature To Confluence

What does Plan A Feature To Confluence do?

Builds a feature specification from scratch with plan-a-feature and publishes it to a user-specified Confluence location, posting the spec as a parent page and each companion artifact (decision log…. Plan A Feature To Confluence is an agent skill from testdouble/han. Builds a feature specification from scratch with plan-a-feature and publishes it to a user-specified Confluence location, posting the spec as a parent page and each companion artifact (decision log, team findings, technical notes) as a child page beneath it.

When should I use Plan A Feature To Confluence?

Plan A Feature To Confluence fits situations like: the user wants a new feature planned; specified AND posted to a Confluence space.

How do I install Plan A Feature To Confluence in Claude Code?

Run `npx skills add testdouble/han --skill plan-a-feature-to-confluence -a claude-code`. Or copy the skill folder (han-atlassian/skills/plan-a-feature-to-confluence in testdouble/han) into .claude/skills/plan-a-feature-to-confluence in your project. Claude Code loads it when a task matches its description.

How do I install Plan A Feature To Confluence in Codex?

Run `npx skills add testdouble/han --skill plan-a-feature-to-confluence -a codex`. Or copy the skill folder (han-atlassian/skills/plan-a-feature-to-confluence in testdouble/han) into .agents/skills/plan-a-feature-to-confluence in your project. Codex loads it when a task matches its description.

Can I use Plan A Feature To Confluence in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add testdouble/han --skill plan-a-feature-to-confluence -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/plan-a-feature-to-confluence, .gemini/skills/plan-a-feature-to-confluence, .github/skills/plan-a-feature-to-confluence and .opencode/skills/plan-a-feature-to-confluence in your project.

What does Plan A Feature To Confluence need to run?

Going by SKILL.md and its folder, Plan A Feature To Confluence needs the command-line tools its instructions call (bash). Its frontmatter pre-approves these tools: Read, Write, Edit, Glob, Grep, Skill, Bash(find *), mcp__claude_ai_Atlassian__getAccessibleAtlassianResources, Bash(bash "${CLAUDE_PLUGIN_ROOT}/scripts/han-config-dir.sh").

Does Plan A Feature To Confluence access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Plan A Feature To Confluence safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Plan A Feature To Confluence use?

Plan A Feature To Confluence is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Plan A Feature To Confluence use?

About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Plan A Feature To Confluence?

Skills that share tags, products or a category with Plan A Feature To Confluence: Grill With Docs (meain/dotfiles, 285 stars), Grill With Docs (ayoubben18/ab-method, 192 stars), Grill With Docs (alirezarezvani/claude-skills, 28k stars) and Model Domain (danielvm-git/bigpowers, 257 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Plan A Feature To Confluence?

testdouble (a GitHub organization) maintains it in testdouble/han, which has 279 GitHub stars. The repository holds 54 skills in this directory. The repository was last updated on October 1, 2026.

Source: testdouble/han on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.