Feedback Intake

OrganizationPopular

nimbalyst

feedback-intake

Help the user file a bug report or feature request for Nimbalyst. Activates when the user opens the in-app feedback flow or runs /feedback:bug-report or /feedback:feature-request. Coordinates evidence gathering, anonymization, and posting to GitHub Issues.

Overview

Publisher	nimbalyst
Repository	`nimbalyst`
Skill name	`feedback-intake`
Stars	1.9K
Forks	300
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 nimbalyst on GitHub. Read the source before you install it.

Installation

Install the Feedback Intake AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/nimbalyst/nimbalyst/tree/main/packages/extensions/feedback/claude-plugin/skills/feedback-intake
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/nimbalyst/nimbalyst/tree/main/packages/extensions/feedback/claude-plugin/skills/feedback-intake

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/nimbalyst/nimbalyst.git /tmp/nimbalyst
mkdir -p .claude/skills
cp -r /tmp/nimbalyst/packages/extensions/feedback/claude-plugin/skills/feedback-intake .claude/skills/feedback-intake

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Feedback Intake 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 Feedback Intake 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 Feedback Intake 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.

Nimbalyst Feedback Skill

This skill is the entry point for the Nimbalyst in-app feedback flow. It activates when:

The user runs the /feedback:bug-report slash command
The user runs the /feedback:feature-request slash command
The user opens a session with sessionType: 'bug-report' or sessionType: 'feature-request'

Behavior

Read the matching command file:

For bug reports: commands/bug-report.md in this plugin
For feature requests: commands/feature-request.md in this plugin

Both commands share these constraints:

The user is the gate. Never call mcp__nimbalyst-situational__feedback_open_github_issue without explicit user approval of the final title and body.
Anonymize aggressively. Run anything that includes file paths, log content, environment strings, or workspace identifiers through mcp__nimbalyst-situational__feedback_anonymize_text first, then read the output and redact anything else that looks sensitive.
Honor the intake flags. Bug-report sessions include Log gathering: allowed or Log gathering: not allowed; feature-request sessions may include UX mockup: requested or UX mockup: not requested. Only bug reports may read logs, and only when log gathering is allowed.
Handle long reports. When the drafted body exceeds the URL safe length, the URL builder returns reason: 'too-long'. Fall back to: show the body in chat, open a no-body URL, tell the user to paste.
Target repo and templates. Bug reports use bug_report.yml; feature requests use feature_request.yml. Both target nimbalyst/nimbalyst. Don't hardcode the URL — let the URL builder handle template selection and field-id routing. The GitHub issue type (Bug / Feature) and status:needs-triage label come from the template frontmatter, not from the URL builder.

Tools available

mcp__nimbalyst-situational__feedback_anonymize_text(text) → returns anonymized string
mcp__nimbalyst-situational__feedback_get_environment() → app version, OS, recent error counts
mcp__nimbalyst-situational__feedback_open_github_issue({ kind, title, body }) → opens GitHub new-issue page in browser, returns { ok, opened, reason?, url? }
mcp__nimbalyst-extension-dev__get_main_process_logs({ lastLines, searchTerm, logLevel, component }) → only with consent
mcp__nimbalyst-extension-dev__get_renderer_debug_logs({ lastLines, searchTerm, logLevel }) → only with consent

Important

Don't add "generated by AI" or "Co-Authored-By" lines to the issue body.
Don't claim the issue was submitted; the user clicks Submit on github.com themselves.
If the user pivots from a bug to a feature mid-conversation (or vice versa), say so and switch templates.

Frequently asked questions

What does the Feedback Intake AI skill do?

Why use Feedback Intake on TypingMind?

Because you install it once and use it with any model. Feedback Intake 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 Feedback Intake in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nimbalyst/nimbalyst/tree/main/packages/extensions/feedback/claude-plugin/skills/feedback-intake. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Feedback Intake?

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 Feedback Intake?

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

Is the Feedback Intake AI skill free?

Yes. It is published on GitHub by nimbalyst 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Nimbalyst Feedback Skill

Behavior

Tools available

Important

Frequently asked questions

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