bp-plugin-discover

name	bp-plugin-discover
description	This skill should be used when the user asks to "find skills", "list skills", "show skill inventory", "what skills exist", "discover skills", "scan plugin for skills", "inventory skills", "show coverage", or needs to see the skill inventory and workflow coverage across a plugin. Triggers on "discover skills", "plugin discover", "list skills", "skill inventory", "scan plugin", "show skills", "coverage report".
allowed-tools	Read, Glob, Grep, AskUserQuestion

Discover & Classify Plugin Skills

Scan a plugin for all SKILL.md files, classify each by workflow coverage level (none, partial, full), check inputs/outputs completeness, and produce a structured inventory for use by other skills.

Classification Algorithm: patterns/classification-algorithm.md Skill Analysis Pattern: ${CLAUDE_PLUGIN_ROOT}/patterns/skill-analysis.md

---

Overview

This skill performs a full discovery pass over a plugin (or multiple locations) and produces a typed inventory. The output feeds downstream skills such as bp-skill-analyze (deep-dive on a single skill) and bp-plugin-batch (bulk operations).

Coverage classifications produced:

Coverage	Meaning	Action
none	All phases are prose — no workflows/ directory or workflow files	Formalization candidates
partial	Some phases delegate to workflows, others remain prose	Review extraction candidates
full	All phases delegate to workflow files in workflows/	Already formalized

Additional flags:

Flag	Meaning
inputs_defined	SKILL.md frontmatter has inputs: array
outputs_defined	SKILL.md frontmatter has outputs: array
legacy_layout	Has bare workflow.yaml sibling instead of workflows/ subdirectory

---

Phase 1: Locate Skills

Step 1.1: Determine Search Scope

Present the user with scope options. Use AskUserQuestion to capture the choice:

{
  "questions": [{
    "question": "Where should I search for skills?",
    "header": "Search Scope",
    "multiSelect": false,
    "options": [
      {
        "label": "Current plugin",
        "description": "Scan skills/ in this plugin directory"
      },
      {
        "label": "User-level skills",
        "description": "Scan ~/.claude/skills/"
      },
      {
        "label": "Installed plugins",
        "description": "Scan ~/.claude/plugins/*/skills/"
      },
      {
        "label": "All locations",
        "description": "Scan current plugin, user skills, and installed plugins"
      }
    ]
  }]
}

Response handling:

HANDLE_SCOPE(response):
  SWITCH response:
    CASE "Current plugin":
      computed.search_scope = "plugin"
      computed.search_roots = [CLAUDE_PLUGIN_ROOT]
    CASE "User-level skills":
      computed.search_scope = "user"
      computed.search_roots = ["~/.claude/skills"]
    CASE "Installed plugins":
      computed.search_scope = "installed"
      computed.search_roots = ["~/.claude/plugins"]
    CASE "All locations":
      computed.search_scope = "all"
      computed.search_roots = [CLAUDE_PLUGIN_ROOT, "~/.claude/skills", "~/.claude/plugins"]

Store the selected scope in computed.search_scope and root paths in computed.search_roots.

Step 1.2: Find All SKILL.md Files

For each search root, use Glob to locate SKILL.md files:

FIND_SKILLS(search_roots):
  computed.skill_files = []

  FOR root IN search_roots:
    IF computed.search_scope == "plugin" OR computed.search_scope == "all":
      files = Glob(root + "/skills/*/SKILL.md")
      computed.skill_files += files

    IF computed.search_scope == "user" OR computed.search_scope == "all":
      files = Glob(root + "/*/SKILL.md")
      computed.skill_files += files

    IF computed.search_scope == "installed" OR computed.search_scope == "all":
      files = Glob(root + "/*/skills/*/SKILL.md")
      computed.skill_files += files

  # Deduplicate by absolute path
  computed.skill_files = deduplicate(computed.skill_files)

  # For each file, extract metadata
  FOR file IN computed.skill_files:
    file.directory = parent_directory(file.path)
    file.name = basename(file.directory)
    file.plugin = determine_plugin_name(file.path)

If computed.skill_files is empty, display a message:

No SKILL.md files found in the selected scope. Verify the search path and try again.

Then offer to retry with a different scope or exit.

Store results in computed.skill_files as an array of objects with path, directory, name, and plugin fields.

---

Phase 2: Classify Skills

Step 2.1: Check for Workflow Files

For each skill found, check for workflow files using the new directory layout:

CHECK_WORKFLOWS():
  FOR skill IN computed.skill_files:
    # Check for workflows/ subdirectory (new layout)
    workflow_dir = skill.directory + "/workflows"
    workflow_files = Glob(workflow_dir + "/*.yaml")
    skill.workflow_files = workflow_files
    skill.has_workflows_dir = len(workflow_files) > 0

    # Check for legacy bare workflow.yaml sibling (old layout)
    legacy_path = skill.directory + "/workflow.yaml"
    skill.has_legacy_workflow = file_exists(legacy_path)
    IF skill.has_legacy_workflow:
      skill.legacy_workflow_path = legacy_path

Step 2.2: Analyze SKILL.md Content and Classify

Read each SKILL.md and apply the coverage classification algorithm. The full algorithm is documented in patterns/classification-algorithm.md.

For each skill, read the file content and determine coverage:

CLASSIFY_ALL():
  FOR skill IN computed.skill_files:
    content = Read(skill.path)
    skill.line_count = count_lines(content)
    skill.frontmatter = extract_frontmatter(content)
    skill.coverage = classify_coverage(skill, content)
    skill.metrics = compute_metrics(content)
    skill.inputs_defined = "inputs" IN skill.frontmatter AND len(skill.frontmatter.inputs) > 0
    skill.outputs_defined = "outputs" IN skill.frontmatter AND len(skill.frontmatter.outputs) > 0
    skill.legacy_layout = skill.has_legacy_workflow AND NOT skill.has_workflows_dir

Coverage classification function (summary — see patterns/classification-algorithm.md for full detail):

function classify_coverage(skill, content):
  # Count phases in the SKILL.md body
  phases = detect_phases(content)
  workflow_backed_phases = count_workflow_backed_phases(content, skill)
  total_phases = len(phases)

  IF total_phases == 0:
    return "none"

  IF workflow_backed_phases == 0:
    return "none"        # No phases delegate to workflows
  ELIF workflow_backed_phases == total_phases:
    return "full"        # All phases delegate to workflows
  ELSE:
    return "partial"     # Some phases are prose, some are workflow-backed

Store classification in computed.skills[] with the coverage field set.

Step 2.3: Compute Phase Metrics

For each skill, compute per-phase metrics:

function compute_metrics(content):
  metrics = {
    line_count:        count_lines(content),
    section_count:     count_matches(content, /^##+ /m),
    phase_count:       count_phases(content),
    workflow_phases:   count_workflow_backed_phases(content),
    prose_phases:      phase_count - workflow_phases,
    conditional_count: count_matches(content, /\b(if|when|otherwise|based on|depending on)\b/i),
    user_prompts:      count_matches(content, /"questions"\s*:\s*\[/) + count_matches(content, /AskUserQuestion/i),
    tool_refs:         count_unique_tools(content)
  }
  return metrics

Complexity thresholds (for prose phases):

Metric	Low	Medium	High
Line count	< 100	100-300	> 300
Phase count	1-2	3-5	6+
Conditionals	0-2	3-6	7+
User prompts	0-1	2-3	4+

---

Phase 3: Generate Inventory

Step 3.1: Build Status Table

Construct a markdown summary table from computed.skills[]:

## Skill Discovery: {computed.plugin_name}

Scanned: {len(computed.skills)} skills
Location: {computed.search_scope}
Timestamp: {computed.discovery.timestamp}

| # | Skill | Coverage | Phases | Workflow Phases | I/O | Layout | Lines | Notes |
|---|-------|----------|--------|-----------------|-----|--------|-------|-------|
{for i, skill in enumerate(computed.skills)}
| {i+1} | {skill.name} | {skill.coverage} | {skill.metrics.phase_count} | {skill.metrics.workflow_phases} | {skill.inputs_defined}/{skill.outputs_defined} | {skill.legacy_layout ? "legacy" : "current"} | {skill.metrics.line_count} | {skill.notes} |
{/for}

Display this table to the user immediately.

Step 3.2: Group by Coverage

After the summary table, present skills grouped by coverage level:

### Full Coverage ({count_full})

All phases delegate to workflow definitions:

{for skill in computed.skills where skill.coverage == "full"}
- **{skill.name}** — {skill.metrics.phase_count} phases, {len(skill.workflow_files)} workflow files
{/for}

### Partial Coverage ({count_partial})

Some phases are workflow-backed, others remain prose:

{for skill in computed.skills where skill.coverage == "partial"}
- **{skill.name}** — {skill.metrics.workflow_phases}/{skill.metrics.phase_count} phases formalized, {skill.metrics.prose_phases} prose phases remaining
{/for}

### No Coverage ({count_none})

All phases are prose — no workflow definitions:

{for skill in computed.skills where skill.coverage == "none"}
- **{skill.name}** — {skill.metrics.phase_count} phases, {skill.metrics.conditional_count} conditionals
{/for}

Step 3.3: Generate Recommendations

Based on the inventory, produce actionable recommendations:

Formalization Opportunities — Prose phases with high extraction scores:

FORMALIZATION_OPPORTUNITIES():
  candidates = []
  FOR skill IN computed.skills:
    IF skill.coverage IN ("none", "partial"):
      FOR phase IN skill.prose_phases:
        score = calculate_extraction_score(phase)
        IF score >= 3:
          candidates.append({skill: skill.name, phase: phase.title, score: score})
  return sorted(candidates, key=lambda c: c.score, reverse=True)

Display:

#### Formalization Opportunities
These prose phases are strong candidates for workflow extraction:

{for candidate in formalization_opportunities}
- **{candidate.skill}** → Phase: {candidate.phase} (extraction score: {candidate.score})
{/for}

Completeness Gaps — Skills missing inputs/outputs definitions:

#### Completeness Gaps
These skills are missing inputs/outputs in their frontmatter:

{for skill in computed.skills where not skill.inputs_defined or not skill.outputs_defined}
- **{skill.name}** — inputs: {skill.inputs_defined}, outputs: {skill.outputs_defined}
{/for}

Legacy Layout — Skills using old bare workflow.yaml instead of workflows/ subdirectory:

#### Legacy Layout
These skills use the old layout (bare workflow.yaml) and should migrate to workflows/ subdirectory:

{for skill in computed.skills where skill.legacy_layout}
- **{skill.name}** — {skill.legacy_workflow_path}
{/for}

Step 3.4: Store Discovery State

Persist the full inventory in computed.discovery for downstream skill consumption:

STORE_DISCOVERY():
  computed.discovery = {
    timestamp:    current_iso_timestamp(),
    plugin_path:  computed.search_roots[0],
    search_scope: computed.search_scope,
    total_skills: len(computed.skills),
    skills:       computed.skills,
    summary: {
      none:    count(s for s in computed.skills if s.coverage == "none"),
      partial: count(s for s in computed.skills if s.coverage == "partial"),
      full:    count(s for s in computed.skills if s.coverage == "full")
    },
    completeness: {
      inputs_defined:  count(s for s in computed.skills if s.inputs_defined),
      outputs_defined: count(s for s in computed.skills if s.outputs_defined),
      legacy_layout:   count(s for s in computed.skills if s.legacy_layout)
    },
    recommendations: {
      formalization_opportunities: formalization_opportunities_list,
      completeness_gaps:           completeness_gaps_list,
      legacy_layout:               legacy_layout_list
    }
  }

---

Phase 4: Offer Deep Dive

Step 4.1: Next Action

After presenting the inventory, ask the user what they want to do next:

{
  "questions": [{
    "question": "What would you like to do next?",
    "header": "Next Steps",
    "multiSelect": false,
    "options": [
      {
        "label": "Analyze a specific skill",
        "description": "Run deep structural analysis on one skill from the inventory"
      },
      {
        "label": "Export discovery report",
        "description": "Save the full inventory to a YAML or Markdown file"
      },
      {
        "label": "Done",
        "description": "No further action needed"
      }
    ]
  }]
}

Response handling:

HANDLE_NEXT_ACTION(response):
  SWITCH response:
    CASE "Analyze a specific skill":
      GOTO Step 4.2
    CASE "Export discovery report":
      GOTO Step 4.3
    CASE "Done":
      DISPLAY "Discovery complete. {computed.discovery.total_skills} skills inventoried."
      EXIT

Step 4.2: Hand Off to Deep Analysis

If the user selects "Analyze a specific skill":

1. Present a follow-up AskUserQuestion listing skills that have prose phases (since fully-formalized skills may not need analysis):

   BUILD_ANALYSIS_OPTIONS():
     analyzable = [s for s in computed.skills
                   if s.coverage in ("none", "partial")]
     options = [{ label: s.name, description: s.coverage + " / " + str(s.metrics.phase_count) + " phases" } for s in analyzable]
   

2. Once the user selects a skill, describe the handoff:

   To perform deep analysis on {selected_skill.name}, invoke:

   Skill(skill: "bp-skill-analyze", args: "{selected_skill.path}")
   

   The skill-analyze skill will identify phases, compute extraction scores, assess workflow quality, and produce a detailed analysis report.

3. Store the selected skill path in computed.analysis_target for downstream use.

Step 4.3: Export Report

If the user selects "Export discovery report":

1. Ask for the output format and location:

   default_path = computed.search_roots[0] + "/docs/skill-discovery-report"
   

2. Generate the report file:

   • YAML format: Serialize computed.discovery as a YAML document
   • Markdown format: Render the grouped inventory tables from Phase 3 as a standalone document

3. Display confirmation:

   Discovery report saved to {output_path}. Contains inventory of {computed.discovery.total_skills} skills with coverage classifications and metrics.

---

Reference Documentation

• Classification Algorithm: patterns/classification-algorithm.md (local to this skill)
• Skill Analysis Pattern: ${CLAUDE_PLUGIN_ROOT}/patterns/skill-analysis.md
• Node Mapping Pattern: ${CLAUDE_PLUGIN_ROOT}/patterns/node-mapping.md
• Authoring Guide: ${CLAUDE_PLUGIN_ROOT}/patterns/authoring-guide.md
• SKILL.md Template: ${CLAUDE_PLUGIN_ROOT}/templates/SKILL.md.template

---

Related Skills

• Deep skill analysis: ${CLAUDE_PLUGIN_ROOT}/skills/bp-skill-analyze/SKILL.md
• Plugin structure analysis: ${CLAUDE_PLUGIN_ROOT}/skills/bp-plugin-analyze/SKILL.md
• Batch operations: ${CLAUDE_PLUGIN_ROOT}/skills/bp-plugin-batch/SKILL.md
• Workflow extraction: ${CLAUDE_PLUGIN_ROOT}/skills/bp-workflow-extract/SKILL.md