Mycelium delivery-bootstrap

Use when starting implementation on a new or unfamiliar codebase. Auto-detects tech stack and sets up development context.

install
source · Clone the upstream repo
git clone https://github.com/haabe/mycelium
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/haabe/mycelium "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.claude/skills/delivery-bootstrap" ~/.claude/skills/haabe-mycelium-delivery-bootstrap && rm -rf "$T"
manifest: .claude/skills/delivery-bootstrap/SKILL.md
source content

Delivery Bootstrap Skill

Just-in-Time tech stack detection and setup.

Workflow

  1. Check product_type from
    diamonds/active.yml
    :
    • If
      product_type
      is set (from
      /interview
      ), use it to determine the delivery profile.
    • If not set, scan for indicators per
      detector.md
      Step 1b:
      • Curriculum/lesson plans, LMS config ->
        content_course
      • Manuscript/chapters, editorial calendar ->
        content_publication
      • Video scripts, subtitle files, podcast RSS ->
        content_media
      • Prompt templates, model configs, agent definitions ->
        ai_tool
      • Service blueprints, pricing docs ->
        service_offering
    • If non-software product_type detected: skip software tooling detection (Steps 2-3 below), configure product-type-appropriate validation instead, and proceed to Step 4.

1b. Scan project root for technology indicators (software and ai_tool with code):

  • Package files: package.json, Cargo.toml, go.mod, requirements.txt, pyproject.toml, Gemfile, pom.xml, build.gradle
  • Config files: tsconfig.json, .eslintrc, .prettierrc, rustfmt.toml, .editorconfig
  • CI/CD: .github/workflows, .gitlab-ci.yml, Jenkinsfile, Dockerfile
  • Framework indicators: next.config.js, nuxt.config.ts, angular.json, etc.
  1. Identify stack components (software/ai_tool with code):

    • Language(s) and version(s)
    • Framework(s)
    • Package manager
    • Test runner and framework
    • Linter and formatter
    • Build tool
    • CI/CD platform
    • Database (if detectable)
    • Deployment target
  2. Verify tooling works:

    • Run build command
    • Run test command
    • Run lint command
    • Note any failures or warnings
  3. Document existing patterns:

    • Code organization (monorepo, src layout, etc.)
    • Naming conventions
    • Test patterns
    • Error handling patterns
    • API patterns
  4. Output:

    ## Stack Profile
    - Language: [x] v[y]
    - Framework: [x]
    - Package manager: [x]
    - Test: [command] ([framework])
    - Lint: [command]
    - Build: [command]
    - CI/CD: [platform]
    
    ## Commands
    - Install: [command]
    - Dev server: [command]
    - Test: [command]
    - Build: [command]
    - Lint: [command]
    
    ## Observed Patterns
    - [list of patterns detected]
    
    ## Issues Found
    - [any broken tooling or warnings]
    

Rules

  • Use the project's established patterns. Don't impose external preferences.
  • Be language-agnostic in principles, language-specific in implementation.
  • If tooling is broken, flag it rather than silently working around it.

Canvas Output

Create/update

.claude/jit-tooling/active-stack.yml
with detected stack configuration. See
.claude/jit-tooling/active-stack.example.yml
for the expected format.

Theory Citations

  • Forsgren: Accelerate (tooling and automation)
  • Smart: Sooner Safer Happier (remove friction)