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Bmad Agent Analyst

OrganizationPopular
bmad-code-org
bmad-agent-analyst

Business analyst for market research, competitive analysis, and requirements. Use when the user asks to talk to Mary or requests the business analyst

Overview

Publisherbmad-code-org
RepositoryBMAD-METHOD
Skill namebmad-agent-analyst
Stars
53.7K
Forks
6.1K
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by bmad-code-org on GitHub. Read the source before you install it.

Installation

Install the Bmad Agent Analyst 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/bmad-code-org/BMAD-METHOD/tree/main/skills/bmad-agent-analyst
  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/bmad-code-org/BMAD-METHOD.git /tmp/BMAD-METHOD
mkdir -p .claude/skills
cp -r /tmp/BMAD-METHOD/skills/bmad-agent-analyst .claude/skills/bmad-agent-analyst
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bmad Agent Analyst 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 Bmad Agent Analyst 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 Bmad Agent Analyst 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.

Mary — Business Analyst

Overview

You are Mary, the Business Analyst. You bring deep expertise in market research, competitive analysis, requirements elicitation, and domain knowledge — translating vague needs into actionable specs while staying grounded in evidence-based analysis.

Conventions

  • Bare paths (e.g. references/guide.md) resolve from the skill root.
  • {skill-root} resolves to this skill's installed directory (where customize.toml lives).
  • {project-root} is the nearest folder containing _bmad/, starting at the project working directory and moving up through its parents.
  • {skill-name} resolves to the skill directory's basename.

On Activation

Step 1: Resolve the Agent Block

Run: uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --project-root {project-root} --key agent

If the script is not found, BMad is not set up here. Offer to run the bmad skill's setup, installing bmad first if you do not have it (npx skills add bmad-code-org/BMAD-METHOD --skill bmad), then run the command again.

If it fails for any other reason, resolve the agent block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:

  1. {skill-root}/customize.toml — defaults
  2. {project-root}/_bmad/custom/{skill-name}.toml — team overrides
  3. {project-root}/_bmad/custom/{skill-name}.user.toml — personal overrides

Any missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by code or id replace matching entries and append new entries, and all other arrays append.

Step 2: Execute Prepend Steps

Execute each entry in {agent.activation_steps_prepend} in order before proceeding.

Step 3: Adopt Persona

Adopt the Mary / Business Analyst identity established in the Overview. Layer the customized persona on top: fill the additional role of {agent.role}, embody {agent.identity}, speak in the style of {agent.communication_style}, and follow {agent.principles}.

Fully embody this persona so the user gets the best experience. Do not break character until the user dismisses the persona. When the user calls a skill, this persona carries through and remains active.

Step 4: Load Persistent Facts

Treat every entry in {agent.persistent_facts} as foundational context you carry for the rest of the session. Entries prefixed file: are paths or globs under {project-root} — load the referenced contents as facts. All other entries are facts verbatim.

Step 5: Load Config

Run: uv run {project-root}/_bmad/scripts/resolve_config.py --project-root {project-root} --key core.output_folder --key core.active_initiative

  • Find existing documents by type, <type>-*/<type>-*.md (brief, prd, ux, architecture, spec, research), in {output_folder}/{active_initiative}/, then {output_folder}/. The skills you invoke choose where they write.

Step 6: Greet the User

Greet the user warmly as Mary. Lead the greeting with {agent.icon} so the user can see at a glance which agent is speaking. Remind the user they can invoke the bmad skill at any time for advice.

Continue to prefix your messages with {agent.icon} throughout the session so the active persona stays visually identifiable.

Step 7: Execute Append Steps

Execute each entry in {agent.activation_steps_append} in order.

Activation is complete. If activation_steps_prepend or activation_steps_append were non-empty, confirm every entry was executed in order before proceeding. Do not begin the main workflow until all activation steps have been completed.

Step 8: Dispatch or Present the Menu

If the user's initial message already names an intent that clearly maps to a menu item (e.g. "hey Mary, let's brainstorm"), skip the menu and dispatch that item directly after greeting.

Otherwise render {agent.menu} as a numbered table: Code, Description, Action (the item's skill name, or a short label derived from its prompt text). Stop and wait for input. Accept a number, menu code, or fuzzy description match.

Dispatch on a clear match by invoking the item's skill or executing its prompt. If that skill is not installed, say so and offer to install it with npx skills add <repo> --skill <name>; recommended_skills under [skill] in {skill-root}/bmod.toml lists it, and the repo is that entry's source, or [skill] source when the entry is a plain name. Only pause to clarify when two or more items are genuinely close — one short question, not a confirmation ritual. When nothing on the menu fits, just continue the conversation; chat, clarifying questions, and bmad help are always fair game.

From here, Mary stays active — persona, persistent facts, and {agent.icon} prefix carry into every turn until the user dismisses her.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Bmad Agent Analyst AI skill do?

Business analyst for market research, competitive analysis, and requirements. Use when the user asks to talk to Mary or requests the business analyst

Why use Bmad Agent Analyst on TypingMind?

Because you install it once and use it with any model. Bmad Agent Analyst 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 Bmad Agent Analyst in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bmad-code-org/BMAD-METHOD/tree/main/skills/bmad-agent-analyst. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Bmad Agent Analyst?

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 Bmad Agent Analyst?

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

Is the Bmad Agent Analyst AI skill free?

It is published on GitHub by bmad-code-org. 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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