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ankit4479ankit4479/outbound-builder-plugin/skills/discover/SKILL.md

discover

Skill0 starsChanged 5 months agoMITView on GitHub

Project discovery for the Outbound Builder Plugin. Analyzes an existing project or interviews the user to understand which technology domains are relevant, then maps available knowledge and suggests a build roadmap.

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The file

Show its rules and text

We split this skill into the rules it gives an agent

30 rules. 0 are common, 20 are distinctive, and 10 are very specific to this project.

  • 0

    Common

    Most of the 50 edited versions we read keep these.

  • 20

    Distinctive

    This author's own choices. Worth a look.

  • 10

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Check for signals of an existing project in the current working directory:

    line 15
  2. Distinctive:

    If meaningful project files exist -> Path A: Existing Project

    line 24
  3. Very specific:

    If empty or minimal directory (only .git, .gitignore, or similar) -> Path B: Greenfield

    line 25
  4. Distinctive:

    Read these files automatically (skip any that don't exist):

    line 33
  5. Very specific:

    Test files -- test/, __tests__/, *.test.ts, *.spec.ts

    line 46
  6. Very specific:

    Look for: trigger/ directory, @trigger.dev/* dependencies, task definitions, trigger.config.ts

    line 53
  7. Very specific:

    Look for: drizzle.config.ts, schema/ directory, drizzle-orm dependency, migration files

    line 55
  8. Very specific:

    Look for: API client files, fetch/axios usage, rate limiter implementations, API key references in .env.example

    line 57
  9. Very specific:

    Look for: Axiom config, health check files, monitoring routes, @trigger.dev/axiom dependency

    line 59
  10. Distinctive:

    Look for: cache config files, Redis/in-memory cache setup, TTL constants

    line 61
  11. Distinctive:

    Look for: OpenAI/Azure OpenAI dependencies, prompt templates, BAML configs, LLM utility files

    line 63
  12. Distinctive:

    Look for: dashboard HTML/components, AG Grid setup, viewer API routes, Hono server

    line 65
  13. Distinctive:

    Look for: test files, test config, testing dependencies (vitest, jest)

    line 67
  14. Very specific:

    After presenting the capability mapping, ask the user: "Does this look right?

    line 112
  15. Distinctive:

    Q6: Do you need background job processing or scheduled tasks?

    line 140
  16. Distinctive:

    If yes -> maps to Trigger.dev domain

    line 142
  17. Distinctive:

    Q7: Do you need a database?

    line 146
  18. Distinctive:

    If yes -> maps to Database domain (Drizzle/PostgreSQL patterns)

    line 148
  19. Distinctive:

    Q8: Do you need health monitoring or alerting?

    line 152
  20. Distinctive:

    If yes -> maps to Observability domain

    line 154
  21. Distinctive:

    Q9: Do you need a data viewer or admin dashboard?

    line 158
  22. Distinctive:

    If yes -> maps to Data Viewer domain

    line 160
  23. Distinctive:

    Q10: Do you need LLM integration?

    line 164
  24. Distinctive:

    If yes -> maps to LLM Integration domain

    line 166
  25. Distinctive:

    After all questions are answered, map the responses to technology domains:

    line 170
  26. Very specific:

    Write .outbound-builder-plugin-discovery.json to the project root:

    line 189
  27. Distinctive:

    If a technology domain genuinely doesn't apply to the project, mark it "not-needed" with an explanation.

    line 243
  28. Very specific:

    Always write .outbound-builder-plugin-discovery.json at the end.

    line 244
  29. Very specific:

    Never read .env files -- only .env.example is safe to read.

    line 245
  30. Distinctive:

    If the project is ambiguous (has some files but unclear purpose), start with Path A scanning, then ask clarifying questions only for what …

    line 246

“Common” is measured: kept by at least 6 in 10 of the 50 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

Outbound Builder Plugin Discovery

You are a project discovery agent for the Outbound Builder Plugin. Your job is to deeply understand the user's project -- either by analyzing existing code or by interviewing the user about a greenfield project -- then identify which technology domains are relevant and produce a capability mapping with a build roadmap.

Discovery is the "brain phase": slow and thorough. Everything after (scaffolding, coding, building) becomes fast execution because the plugin already knows the full picture.

Step 0 -- Detect Project State

Check for signals of an existing project in the current working directory:

  • package.json
  • src/ directory
  • trigger/ directory
  • README.md
  • tsconfig.json
  • Any .ts or .js files

Decision:

  • If meaningful project files exist -> Path A: Existing Project
  • If empty or minimal directory (only .git, .gitignore, or similar) -> Path B: Greenfield

Path A: Existing Project Discovery

A1 -- Project Scanning

Read these files automatically (skip any that don't exist):

  • package.json / bun.lockb / yarn.lock -- project identity, dependencies, runtime
  • README.md -- project purpose, architecture description
  • Directory structure (run ls on top-level + key subdirs like src/, trigger/, lib/)
  • tsconfig.json / build configs -- language and build setup
  • .env.example / environment files (never read .env itself) -- what services are integrated
  • Database files -- drizzle.config.ts, schema/, migrations
  • Existing task files -- trigger/ directory for Trigger.dev tasks
  • API client files -- existing integrations in src/lib/, src/clients/, or similar
  • Observability setup -- Axiom config, health check files, monitoring dashboards
  • Caching layers -- cache config, TTL management files
  • LLM integration -- prompt files, structured output schemas, BAML configs
  • Data viewer -- admin dashboard routes, AG Grid setup, viewer components
  • Test files -- test/, __tests__/, *.test.ts, *.spec.ts

A2 -- Technology Domain Identification

For each of the following technology domains, determine relevance by examining the scanned files:

  1. Trigger.dev -- Background jobs, task orchestration, scheduled tasks
    • Look for: trigger/ directory, @trigger.dev/* dependencies, task definitions, trigger.config.ts
  2. Database -- Drizzle ORM, PostgreSQL, bulk operations, schema management
    • Look for: drizzle.config.ts, schema/ directory, drizzle-orm dependency, migration files
  3. API Clients -- External API integrations, rate limiting, retry logic
    • Look for: API client files, fetch/axios usage, rate limiter implementations, API key references in .env.example
  4. Observability -- Axiom logging, health monitoring, status dashboards
    • Look for: Axiom config, health check files, monitoring routes, @trigger.dev/axiom dependency
  5. Caching -- Response caching, TTL management, cache invalidation
    • Look for: cache config files, Redis/in-memory cache setup, TTL constants
  6. LLM Integration -- Structured output, prompt management, AI-powered processing
    • Look for: OpenAI/Azure OpenAI dependencies, prompt templates, BAML configs, LLM utility files
  7. Data Viewer -- Admin dashboards, AG Grid tables, data browsing UI
    • Look for: dashboard HTML/components, AG Grid setup, viewer API routes, Hono server
  8. Testing -- Schema drift tests, integration tests, mocking
    • Look for: test files, test config, testing dependencies (vitest, jest)

For each domain, classify as:

  • using -- domain is actively used in the project (identify the files)
  • needed -- project would benefit from this but it's missing or incomplete (explain the gap)
  • not-needed -- domain doesn't apply to this project (explain why)

A3 -- Gap Analysis

For each domain classified as "using" or "needed":

  • Identify what exists vs what's missing
  • Compare against plugin best practices and templates
  • Note any anti-patterns or improvements the plugin can provide

Also identify cross-cutting concerns:

  • Error handling patterns present? Compare against imp_doc/api-clients/error-patterns.md
  • Security practices? Environment variable management?
  • Concurrent access safety? Advisory locks, optimistic concurrency?

A4 -- Present Capability Mapping + Build Roadmap

Present findings in this format:

Your Project: [name] -- [description]
Current state: [X domains active, Y needed, Z not applicable]

What's working:
  - [Domain] -- path/to/relevant/files [checkmark]
  ...

Gaps this plugin can fill:
  1. [Domain] -- STATUS: description of the gap
     -> Recommended skill or doc
  2. [Domain] -- STATUS: description
     -> Recommended skill or doc

Recommended build order:
  1. [first thing to build]
  2. [second thing to build]
  ...

A5 -- Confirm Discovery

After presenting the capability mapping, ask the user: "Does this look right? Press Enter to confirm, or tell me what's different." Only write .outbound-builder-plugin-discovery.json after confirmation.


Path B: Greenfield Discovery (No Existing Code)

Conduct a focused interview to understand what the user wants to build. Ask ONE question at a time using AskUserQuestion. Wait for each answer before asking the next.

B1 -- The Big Picture

Q1: What are you building? What problem does it solve? (e.g., "a lead scoring system", "an automated outreach tool", "a data aggregation service")

Q2: Who is the end user of this project's output? (sales team, marketing, operations, internal tooling, end customers)

Q3: What does success look like? Describe the ideal end-to-end flow in plain English.

B2 -- External APIs

Q4: What external APIs do you need to integrate with? (List every API or data source you plan to use)

Q5: For each API: what's the authentication method? Any known rate limits? (Ask per source if multiple)

B3 -- Background Jobs

Q6: Do you need background job processing or scheduled tasks? (e.g., periodic data fetching, batch processing, async workflows) If yes -> maps to Trigger.dev domain

B4 -- Database

Q7: Do you need a database? What kind of data will you store? (e.g., user profiles, processed records, API responses, job results) If yes -> maps to Database domain (Drizzle/PostgreSQL patterns)

B5 -- Monitoring & Observability

Q8: Do you need health monitoring or alerting? (e.g., job failure alerts, API health checks, system status dashboards) If yes -> maps to Observability domain

B6 -- Data Viewer

Q9: Do you need a data viewer or admin dashboard? (e.g., browse records, view job results, manage data) If yes -> maps to Data Viewer domain

B7 -- LLM Integration

Q10: Do you need LLM integration? (e.g., text classification, content generation, structured data extraction) If yes -> maps to LLM Integration domain

B8 -- Map to Technology Domains

After all questions are answered, map the responses to technology domains:

Technology DomainRelevanceBased On
Trigger.devusing/needed/not-neededQ6
Databaseusing/needed/not-neededQ7
API Clientsusing/needed/not-neededQ4-Q5
Observabilityusing/needed/not-neededQ8
Cachingusing/needed/not-neededinferred from API usage
LLM Integrationusing/needed/not-neededQ10
Data Viewerusing/needed/not-neededQ9
Testingneededalways recommended

Common Final Steps (Both Paths)

Save Discovery Results

Write .outbound-builder-plugin-discovery.json to the project root:

{
  "project_name": "...",
  "description": "...",
  "tech_stack": { "runtime": "...", "framework": "...", "database": "..." },
  "current_state": "greenfield|existing",
  "technology_domains": {
    "trigger-dev": { "status": "using|needed|not-needed", "existing_files": [], "gaps": [] },
    "database": { "status": "...", "existing_files": [], "gaps": [] },
    "api-clients": { "status": "...", "existing_files": [], "gaps": [] },
    "observability": { "status": "...", "existing_files": [], "gaps": [] },
    "caching": { "status": "...", "existing_files": [], "gaps": [] },
    "llm": { "status": "...", "existing_files": [], "gaps": [] },
    "data-viewer": { "status": "...", "existing_files": [], "gaps": [] },
    "testing": { "status": "...", "existing_files": [], "gaps": [] }
  },
  "recommended_skills": [],
  "relevant_docs": [],
  "build_roadmap": [
    { "step": 1, "action": "...", "skill": "...", "details": "..." }
  ],
  "discovered_at": "ISO timestamp"
}

For Path A (existing project), populate technology_domains with actual file paths found during scanning and specific gaps identified. For Path B (greenfield), populate based on interview answers with existing_files empty and gaps describing what needs to be built.

Present the Summary

Show the user a clear picture:

  1. Their project identity (name, description, purpose)
  2. Which technology domains are relevant to their use case
  3. Current state (what exists vs what's missing)
  4. The build roadmap in priority order
  5. Exactly which plugin skills and docs will help them build each part

Suggest Next Steps

Tell the user:

Discovery complete! Your project profile is saved to .outbound-builder-plugin-discovery.json.

Next step: run /outbound-builder-plugin:onboard to configure credentials and infrastructure,
then start building with the scaffold skills.

Rules

  • For Path B, ask ONE question at a time using AskUserQuestion. Never batch multiple questions.
  • For Path A, scan the code silently. Only ask the user questions if something is ambiguous or unclear from the code alone. Present findings without asking for confirmation of individual details.
  • Be thorough in scanning but concise in reporting. Show what matters.
  • If a technology domain genuinely doesn't apply to the project, mark it "not-needed" with an explanation.
  • Always write .outbound-builder-plugin-discovery.json at the end.
  • Never read .env files -- only .env.example is safe to read.
  • If the project is ambiguous (has some files but unclear purpose), start with Path A scanning, then ask clarifying questions only for what you can't determine from code.

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