Writing Release Notes logo

Writing Release Notes

Organization
bitwarden
writing-release-notes

Write user-facing release notes for a Bitwarden release from a Jira release tag and the

Overview

Publisherbitwarden
Repositoryai-plugins
Skill namewriting-release-notes
Stars
149
Forks
19
Bundled files
Instructions only
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 bitwarden on GitHub. Read the source before you install it.

Installation

Install the Writing Release Notes 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.
  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/bitwarden/ai-plugins.git /tmp/ai-plugins
mkdir -p .claude/skills
cp -r /tmp/ai-plugins/plugins/bitwarden-product-analyst/skills/writing-release-notes .claude/skills/writing-release-notes
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Writing Release Notes 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 Writing Release Notes 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 Writing Release Notes 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.

Writing Release Notes

Produce concise, user-facing release notes for a Bitwarden release. The output is what customers read — on GitHub, in the App Store, or in Google Play — so every word should be benefit-oriented, jargon-free, and accurate about what users will actually experience.

Prerequisites

Automated Jira lookups require the bitwarden-atlassian-tools plugin (its MCP server exposes search_issues, get_issue, and get_issue_comments). Without it, or when running in a Claude.ai Project (MCP tools are unavailable there), fall back to asking the user to paste the release page content and the Slack thread text directly — the rest of this skill works identically either way. There is no Slack MCP integration in this marketplace; the Slack thread is always gathered by asking the user to paste it.

Step 1: Gather Inputs

Gather two inputs before writing anything:

1a. Jira Release Page

Ask the user for the Jira release page URL (e.g. https://bitwarden.atlassian.net/projects/CL/versions/12345/tab/release-report-all-issues) or the release version name (e.g. 2025.7.0).

If search_issues is available, resolve the query:

  • From a URL, extract the numeric version ID (the segment after /versions/) and query by ID: fixVersion = 12345 ORDER BY issuetype ASC
  • From a version name, quote it: fixVersion = "2025.7.0" ORDER BY issuetype ASC

Call search_issues with fields: ["summary", "issuetype", "labels", "components", "status", "description"], and page through results using the returned nextPageToken until none is returned. For each issue, capture summary, issue type, labels, components, status, and any feature flag references found in the description. Feature flag references usually surface more completely in the Slack thread (Step 1b); only call get_issue_comments for individual issues where the flag is ambiguous after checking both sources.

If MCP tools are not available (web app context), ask the user to paste the release page content or a list of ticket summaries directly into the conversation.

1b. #release Slack Thread

The #release Slack thread is posted weekly and specifies which feature flags are toggled for the release. This is critical for two reasons:

  • Include: Only user-facing changes whose feature flag is being enabled in this release (or that have no flag) should appear in the notes.
  • Flags enabled with no matching issue in this release: don't assume there's nothing to report — see the Step 3 investigation.
  • Server releases — flag removals: When a feature flag is being fully removed from the server codebase, this signals that self-hosted users are gaining access to the feature. These must appear in the release notes.

Ask the user to paste the thread content.

Parse the thread to extract:

  • Release version and date
  • List of flags being enabled for this release (per platform if specified)
  • List of flags being removed (for server releases — capture both the flag identifier and any associated feature description from the ticket or thread)
  • Any PM or engineering notes about what to highlight or suppress

Step 2: Determine Release Scope

Identify:

  • Which repo/product is being released (clients, server, mobile, browser extension, CLI, desktop)
  • Which platforms are covered (web app, desktop, browser extension, mobile iOS, mobile Android, CLI)
  • Release version number

If the release covers multiple repos with separate release notes (e.g., clients and server each have their own GitHub release), confirm with the user whether they want notes for all or one.

Step 3: Filter to User-Facing Changes

Go through every issue in the release and classify it. Only items that pass the filter appear as named bullet points.

Include as a named bullet point

  • New user-visible features or capabilities
  • UI or UX changes users will notice
  • Policy and admin setting changes (including new enforcement options)
  • Performance improvements users will perceive
  • Significant accessibility improvements
  • New onboarding flows, product tours, or setup wizards
  • Checkout, billing, or subscription flow changes
  • Items whose feature flag is confirmed enabled in this release's Slack thread
  • Flags confirmed enabled in the Slack thread with no matching issue in this release's Jira list, but only once the investigation below shows the guarded feature is itself user-facing

Collapse into the catch-all line

  • Internal refactors, code cleanup, or architecture changes with no user-visible effect
  • Dependency upgrades with no user-visible change
  • Test coverage additions
  • Logging, telemetry, or analytics instrumentation
  • Items behind a feature flag that is not being enabled in this release
  • Flags confirmed enabled in this release whose guarded work turns out to be an internal refactor, infrastructure change, or other item that would collapse under these same rules if it had shipped with a ticket in this release
  • Minor copy or label tweaks not worth their own bullet
  • Bug fixes that are too narrow or edge-case to be meaningful to most users

Always include (never collapse) — server releases only

Feature flags that are fully removed from the server codebase in this release. Flag removal is the moment self-hosted users gain access to a feature. Write each removal as a user-facing line describing what the feature does — not the internal flag identifier. See Step 4 for format.

Investigate — flags enabled without a matching release issue

For every flag the Slack thread lists as enabled, check whether any issue gathered in Step 1a references it. If none do, the underlying work may have shipped in an earlier release and is only now going live (reportable), or it may guard an internal refactor or infrastructure change that was never going to be user-facing (collapses like any other item in that category).

Resolve what the flag guards, in this order:

  1. Search Jira for the flag identifier as free text, without restricting to this release's fixVersion (e.g. text ~ "flag-identifier" ORDER BY created ASC), to find the ticket(s) that originally implemented the feature.
  2. If a ticket is found, run its summary/description back through the Include / Collapse / Exclude filter above. Judge whether the guarded work itself is user-visible.
  3. If nothing turns up, or if search_issues is unavailable, ask the user for a one-line description of what the flag enables, and classify that description the same way — do not guess or invent functionality.

If the filter says it's user-facing, write a plain-language line about the feature going live (Step 4 format rules). If the filter says it collapses or excludes, let it fall into the catch-all line or drop it, same as any other item in that category.

Exclude entirely

  • Security fixes, unless the Slack thread or the user explicitly approves specific wording for one (default to excluding all security fixes from named bullets)
  • Internal tooling changes with zero user impact
  • Duplicate or reverted changes

Step 4: Write the Release Notes

Format rules

  • Plain text only — no markdown, no asterisks, no headers, no bullet characters
  • One line per notable change
  • Begin each line with a past-tense action verb: Added, Updated, Fixed, Improved, Removed
  • Write from the user's perspective — what did they gain, lose, or notice?
  • No Jira ticket numbers, no internal terminology, and critically: no feature flag identifiers
  • Keep each line under ~12 words
  • Aim for 3–7 notable bullet points maximum, followed by one catch-all line
  • End with: Various under-the-hood improvements and minor bug fixes

Tone

Informative, brief, benefit-forward. Avoid marketing superlatives ("exciting", "powerful"). Avoid engineering jargon ("refactored", "migrated", "scaffolded", "deprecated"). Write for a non-technical user who wants to know if anything changed that affects them.

Server flag removals

Flag removal lines describe the feature the flag was guarding, in plain user-facing language. Look up the associated Jira ticket, Confluence page, or Slack thread description to find the right framing. The internal flag name is a lookup key only — it never appears in the output.

Use the format:

Removed feature flag for [user-facing description of what the feature does]

Example: a flag named pm-36859-refactor-org-collections-vault-component becomes:

Removed feature flag for organization vault collection management improvements

Self-hosted users are the primary audience for this line — they are receiving the feature for the first time when the flag is removed, so the description should communicate the benefit clearly.

Flags enabled for previously-shipped work

When a flag in the Slack thread's enabled list has no matching issue in this release, and the Step 3 investigation shows the guarded work is genuinely user-facing, write a normal named bullet describing the feature going live — phrased the same as any other Added/Updated line. Do not call out that it was "previously shipped" or reference the flag mechanics; users only care that the feature is now available to them.

Example: the Slack thread lists pm-40021-item-share-preview as enabled, but every issue tagged with that flag shipped two releases ago and none appear in this release's Jira list. A Jira search for the flag identifier turns up the original ticket, "Add preview before sharing vault items" — a user-facing change, so it earns a bullet. The resulting line:

Added a preview step before sharing vault items

Not every enabled flag reaches this point. If the same investigation instead turns up a ticket like "Refactor vault item sharing internals behind a flag," it collapses into the catch-all line exactly as it would have if it had shipped with a ticket in this release.

Example output (clients release)

Updated UI for centralized ownership policy
Added a product tour for access intelligence
Added information banner to SCIM setup page
Added a checkout success page following Stripe payment flows
Various under-the-hood improvements and minor bug fixes

Example output (server release with flag removals)

Added support for flexible collection permissions for enterprise plans
Improved admin console filtering for large organizations
Removed feature flag for flexible collection permission management
Removed feature flag for bulk collection management improvements
Various under-the-hood improvements and minor bug fixes

Step 5: Review and Calibrate

Before presenting the final output, check:

  • Every named bullet has its corresponding feature flag enabled in the Slack thread (or has no flag)
  • Every flag in the Slack thread's enabled list has been checked against this release's Jira issues
  • Any flag with no matching issue was resolved by lookup or by asking the user, then given a bullet, collapsed, or excluded
  • No internal or infrastructure-only changes appear as named bullets
  • Server releases include a line for every flag removal mentioned in the Slack thread, written in user-facing language
  • No internal flag identifiers appear anywhere in the output
  • Total named bullets are between 3 and 7 (if more than 7 are equally important, consolidate similar items)
  • The catch-all line is present
  • No markdown formatting in the output text

Frequently asked questions

What does the Writing Release Notes AI skill do?

Write user-facing release notes for a Bitwarden release from a Jira release tag and the

Why use Writing Release Notes on TypingMind?

Because you install it once and use it with any model. Writing Release Notes 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 Writing Release Notes in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bitwarden/ai-plugins/tree/main/plugins/bitwarden-product-analyst/skills/writing-release-notes. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Writing Release Notes?

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 Writing Release Notes?

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

Is the Writing Release Notes AI skill free?

It is published on GitHub by bitwarden. Check the repository for licensing terms. 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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