agentleFS
PaulKnauerPaulKnauer/sonos-mcp-server/.agents/skills/bmad-domain-research/SKILL.md

bmad-domain-research

Skill1 starsChanged 4 months agoApache-2.0View on GitHub

Conduct domain and industry research. Use when the user says wants to do domain research for a topic or industry

We split this skill into the rules it gives an agent

9 rules. 0 are common, 2 are distinctive, and 7 are very specific to this project.

  • 0

    Common

    Most of the 10 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 7

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    ⛔ Web search required: If unavailable, abort and tell the user.

    line 21
  2. Very specific:

    Treat every entry in {workflow.persistent_facts} as foundational context you carry for the rest of the workflow run.

    line 43
  3. Very specific:

    Use {user_name} for greeting

    line 48
  4. Very specific:

    Use {communication_language} for all communications

    line 49
  5. Very specific:

    Use {document_output_language} for output documents

    line 50
  6. Very specific:

    Use {planning_artifacts} for output location and artifact scanning

    line 51
  7. Very specific:

    Use {project_knowledge} for additional context scanning

    line 52
  8. Distinctive:

    After gathering the topic and goals:

    line 85
  9. Very specific:

    Create the starter output file: {planning_artifacts}/research/domain-{{research_topic_slug}}-research-{{date}}.md with exact copy of the …

    line 91

“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Domain Research Workflow

Goal: Conduct comprehensive domain/industry research using current web data and verified sources to produce complete research documents with compelling narratives and proper citations.

Your Role: You are a domain research facilitator working with an expert partner. This is a collaboration where you bring research methodology and web search capabilities, while your partner brings domain knowledge and research direction.

Conventions

  • Bare paths (e.g. domain-steps/step-01-init.md) resolve from the skill root.
  • {skill-root} resolves to this skill's installed directory (where customize.toml lives).
  • {project-root}-prefixed paths resolve from the project working directory.
  • {skill-name} resolves to the skill directory's basename.

PREREQUISITE

⛔ Web search required. If unavailable, abort and tell the user.

On Activation

Step 1: Resolve the Workflow Block

Run: python3 {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow

If the script fails, resolve the workflow 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 {workflow.activation_steps_prepend} in order before proceeding.

Step 3: Load Persistent Facts

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

Step 4: Load Config

Load config from {project-root}/_bmad/bmm/config.yaml and resolve:

  • Use {user_name} for greeting
  • Use {communication_language} for all communications
  • Use {document_output_language} for output documents
  • Use {planning_artifacts} for output location and artifact scanning
  • Use {project_knowledge} for additional context scanning

Step 5: Greet the User

Greet {user_name}, speaking in {communication_language}.

Step 6: Execute Append Steps

Execute each entry in {workflow.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.

QUICK TOPIC DISCOVERY

"Welcome {{user_name}}! Let's get started with your domain/industry research.

What domain, industry, or sector do you want to research?

For example:

  • 'The healthcare technology industry'
  • 'Sustainable packaging regulations in Europe'
  • 'Construction and building materials sector'
  • 'Or any other domain you have in mind...'"

Topic Clarification

Based on the user's topic, briefly clarify:

  1. Core Domain: "What specific aspect of [domain] are you most interested in?"
  2. Research Goals: "What do you hope to achieve with this research?"
  3. Scope: "Should we focus broadly or dive deep into specific aspects?"

ROUTE TO DOMAIN RESEARCH STEPS

After gathering the topic and goals:

  1. Set research_type = "domain"
  2. Set research_topic = [discovered topic from discussion]
  3. Set research_goals = [discovered goals from discussion]
  4. Derive research_topic_slug from {{research_topic}}: lowercase, trim, replace whitespace with -, strip path separators (/, \), .., and any character that is not alphanumeric, -, or _. Collapse repeated - and strip leading/trailing -. If the result is empty, use untitled.
  5. Create the starter output file: {planning_artifacts}/research/domain-{{research_topic_slug}}-research-{{date}}.md with exact copy of the ./research.template.md contents
  6. Load: ./domain-steps/step-01-init.md with topic context

Note: The discovered topic from the discussion should be passed to the initialization step, so it doesn't need to ask "What do you want to research?" again - it can focus on refining the scope for domain research.

✅ YOU MUST ALWAYS SPEAK OUTPUT In your Agent communication style with the config {communication_language}

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