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.
- Reads credentials
57 other projects use a version of this.
Adopted by
Most recently taken up by
- anombyte93/prd-taskmastertheir own version, first seen Nov 8, 2026
- charles-adedotun/sre-plugintheir own version, first seen Nov 8, 2026
- rajanrx/skillstheir own version, first seen Nov 8, 2026
- joeldevz/skynex-pitheir own version, first seen Nov 8, 2026
- AsiaOstrich/EngramGraphtheir own version, first seen Nov 8, 2026
- islandhopper81/claude-skillstheir own version, first seen Nov 1, 2026
Used with
Projects with it also use daily-arxiv, exp-eval and 10 more.
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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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skyllwtSkillexp-pilot-run
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phanghonghaoSkillposter
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Also in 4 projects that use this
- +6 more from Lambenthan
- +1 more from skyllwt
Other versions57 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 57
- skyllwt/OmegaWiki★ 1.7ksame name
- DAIR-AutoResearch/AutoSci★ 1.7ksame name
- PKU-DAIR/AutoSci★ 1.7ksame name
- skyllwt/AutoSci★ 1.7ksame name
- suboss87/FDEOps★ 940same name
- anombyte93/prd-taskmaster★ 608same name
- zaxbysauce/opencode-swarm★ 519same name
- ZaxbyHub/opencode-swarm★ 518same name
- hsantanna88/clo-author★ 262same name
- hugosantanna/clo-author★ 262same name
47 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository8 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- browseSkill
- onboardSkill
- rememberSkill
- scaffold-clientSkill
- scaffold-projectSkill
- scaffold-taskSkill
- scaffold-viewerSkill
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
- Distinctive: line 15
Check for signals of an existing project in the current working directory:
- Distinctive: line 24
If meaningful project files exist -> Path A: Existing Project
- Very specific: line 25
If empty or minimal directory (only .git, .gitignore, or similar) -> Path B: Greenfield
- Distinctive: line 33
Read these files automatically (skip any that don't exist):
- Very specific: line 46
Test files -- test/, __tests__/, *.test.ts, *.spec.ts
- Very specific: line 53
Look for: trigger/ directory, @trigger.dev/* dependencies, task definitions, trigger.config.ts
- Very specific: line 55
Look for: drizzle.config.ts, schema/ directory, drizzle-orm dependency, migration files
- Very specific: line 57
Look for: API client files, fetch/axios usage, rate limiter implementations, API key references in .env.example
- Very specific: line 59
Look for: Axiom config, health check files, monitoring routes, @trigger.dev/axiom dependency
- Distinctive: line 61
Look for: cache config files, Redis/in-memory cache setup, TTL constants
- Distinctive: line 63
Look for: OpenAI/Azure OpenAI dependencies, prompt templates, BAML configs, LLM utility files
- Distinctive: line 65
Look for: dashboard HTML/components, AG Grid setup, viewer API routes, Hono server
- Distinctive: line 67
Look for: test files, test config, testing dependencies (vitest, jest)
- Very specific: line 112
After presenting the capability mapping, ask the user: "Does this look right?
- Distinctive: line 140
Q6: Do you need background job processing or scheduled tasks?
- Distinctive: line 142
If yes -> maps to Trigger.dev domain
- Distinctive: line 146
Q7: Do you need a database?
- Distinctive: line 148
If yes -> maps to Database domain (Drizzle/PostgreSQL patterns)
- Distinctive: line 152
Q8: Do you need health monitoring or alerting?
- Distinctive: line 154
If yes -> maps to Observability domain
- Distinctive: line 158
Q9: Do you need a data viewer or admin dashboard?
- Distinctive: line 160
If yes -> maps to Data Viewer domain
- Distinctive: line 164
Q10: Do you need LLM integration?
- Distinctive: line 166
If yes -> maps to LLM Integration domain
- Distinctive: line 170
After all questions are answered, map the responses to technology domains:
- Very specific: line 189
Write .outbound-builder-plugin-discovery.json to the project root:
- Distinctive: line 243
If a technology domain genuinely doesn't apply to the project, mark it "not-needed" with an explanation.
- Very specific: line 244
Always write .outbound-builder-plugin-discovery.json at the end.
- Very specific: line 245
Never read .env files -- only .env.example is safe to read.
- Distinctive: line 246
If the project is ambiguous (has some files but unclear purpose), start with Path A scanning, then ask clarifying questions only for what …
“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.
Files
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.jsonsrc/directorytrigger/directoryREADME.mdtsconfig.json- Any
.tsor.jsfiles
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, runtimeREADME.md-- project purpose, architecture description- Directory structure (run
lson top-level + key subdirs likesrc/,trigger/,lib/) tsconfig.json/ build configs -- language and build setup.env.example/ environment files (never read.envitself) -- 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:
- Trigger.dev -- Background jobs, task orchestration, scheduled tasks
- Look for:
trigger/directory,@trigger.dev/*dependencies, task definitions, trigger.config.ts
- Look for:
- Database -- Drizzle ORM, PostgreSQL, bulk operations, schema management
- Look for:
drizzle.config.ts,schema/directory,drizzle-ormdependency, migration files
- Look for:
- API Clients -- External API integrations, rate limiting, retry logic
- Look for: API client files,
fetch/axiosusage, rate limiter implementations, API key references in.env.example
- Look for: API client files,
- Observability -- Axiom logging, health monitoring, status dashboards
- Look for: Axiom config, health check files, monitoring routes,
@trigger.dev/axiomdependency
- Look for: Axiom config, health check files, monitoring routes,
- Caching -- Response caching, TTL management, cache invalidation
- Look for: cache config files, Redis/in-memory cache setup, TTL constants
- LLM Integration -- Structured output, prompt management, AI-powered processing
- Look for: OpenAI/Azure OpenAI dependencies, prompt templates, BAML configs, LLM utility files
- Data Viewer -- Admin dashboards, AG Grid tables, data browsing UI
- Look for: dashboard HTML/components, AG Grid setup, viewer API routes, Hono server
- 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 Domain | Relevance | Based On |
| Trigger.dev | using/needed/not-needed | Q6 |
| Database | using/needed/not-needed | Q7 |
| API Clients | using/needed/not-needed | Q4-Q5 |
| Observability | using/needed/not-needed | Q8 |
| Caching | using/needed/not-needed | inferred from API usage |
| LLM Integration | using/needed/not-needed | Q10 |
| Data Viewer | using/needed/not-needed | Q9 |
| Testing | needed | always 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:
- Their project identity (name, description, purpose)
- Which technology domains are relevant to their use case
- Current state (what exists vs what's missing)
- The build roadmap in priority order
- 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.jsonat the end. - Never read
.envfiles -- only.env.exampleis 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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