boolean-search-builder

Boolean Search Builder

Pure reasoning skill. Generates sourcing queries tailored per platform. Each platform has different operator syntax — this skill knows them.

Built for: Sourcer or recruiter who needs to find qualified candidates quickly without spray-and-pray.

When to Use

• After scorecard exists and /source command is running
• "Help me find [role] on LinkedIn"
• "Build me a GitHub search for [stack] engineers"

Phase 0: Inputs

Read:

1. clients/<cliente>/jobs/<job-slug>/scorecard.md (must-haves drive query terms)
2. job-description.md (for stack and seniority cues)

Confirm with user:

• Primary platform (LinkedIn, GitHub, X-ray, community)
• Geo target (specific city / country / remote-OK)
• Volume goal (rough number of qualified candidates needed)

Phase 1: Query Strategy by Platform

LinkedIn Recruiter / LinkedIn Sales Nav

Operators: AND, OR, NOT, parentheses, quotes for phrases.

("Senior Software Engineer" OR "Staff Engineer" OR "Senior Backend Engineer")
AND ("Go" OR "Golang" OR "Rust")
AND ("distributed systems" OR "high scale" OR "microservices")
NOT ("intern" OR "junior" OR "manager")

Tips:

• Title field: focus operators here, not "anywhere"
• Skills field: use for tech stack
• Years of experience: 3+ for mid, 5+ for senior, 8+ for staff
• Current company: target companies from sourcing plan
• Past company: for "ex-Google" / "ex-Stripe" patterns

GitHub (for technical roles)

GitHub search via https://github.com/search:

language:Go location:"São Paulo" followers:>50
language:Rust stars:>100 in:bio "engineer"

Useful filters:

• language: (primary language)
• location: (best-effort, many profiles incomplete)
• followers:>N (signal of community presence)
• repos:>N (active developer)
• stars:>N on owned repos (built things people care about)

Signal beyond keywords:

• Recent activity (commits in last 6 months)
• Quality of README in pinned repos
• Open-source contributions to relevant projects (PRs to Kubernetes / Postgres / etc.)
• Personal site / blog linked

X-ray Search (Google site: operators)

For when LinkedIn search limit is hit, or for non-LI profiles:

site:linkedin.com/in "Senior Engineer" "Brazil" ("Go" OR "Rust") -intern
site:github.com/* "engineer" "São Paulo"
site:stackoverflow.com/users "Go" reputation:>1000

Communities

Map common channels per role:

Role	Communities
Backend (Go/Rust)	Gopher Slack, Rust Discord, r/golang, r/rust
Frontend (React)	React Discord, dev.to, r/reactjs
Data / ML	Kaggle, Hugging Face Discord, MLOps Community
DevRel	DevRel Collective Slack
Designers	Designer Hangout, Dribbble, Layers
PMs	Lenny's community, Mind the Product, Reforge alumni
Sales	RevGenius, Pavilion, Sales Hacker

For each community, suggest:

• Search strategy within the community (member search, recent posts, etc.)
• Approach style (DM cold = bad in most communities — engage in public first)

Phase 2: Negative Filters (the underrated half)

Every Boolean search needs NOT clauses to cut noise:

• NOT (intern OR junior OR student) for senior roles
• NOT (founder OR CEO) if targeting ICs
• NOT (recruiter OR sourcer) always (otherwise inbox is half-recruiter)
• Specific competitor companies if poaching restrictions apply

Phase 3: Iteration Plan

Sourcing queries are not one-shot. Plan:

• Iteration 1: Tight query (high precision, low volume) — start with must-haves only
• Iteration 2: Loosen one constraint (e.g., drop one nice-to-have) — see volume jump
• Iteration 3: Adjacent skills (e.g., Rust → C++ if Rust pool too small)

Track which iteration produced which candidates in sourcing-plan.md.

Phase 4: Outreach Hook Hint

For each query bucket, suggest the first-message hook angle:

• "Saw your work on [specific repo/project]" — for GitHub-sourced
• "Your post on [topic] resonated" — for content creators
• "Noticed you're at [company], [specific context]" — for company-targeted
• Generic "we have an exciting opportunity" — refuse. Bad outreach is worse than no outreach.

Phase 5: Output

Append to clients/<cliente>/jobs/<job-slug>/sourcing-plan.md:

## Boolean queries

### LinkedIn — primary
[query]
**Estimated volume:** N profiles
**Filters to apply:** [years exp, geo, current company]

### LinkedIn — adjacent
[loosened query]

### GitHub
[query]

### X-ray fallback
[query]

### Communities
- [Community name]: [search strategy] | [first message angle]

## Iteration plan
1. Start with: [tightest query]
2. If <20 results in 24h, loosen: [...]
3. If still thin: [adjacent stack / role]

## Outreach hooks per source
- LinkedIn: [hook]
- GitHub: [hook]
- Community: [hook]

Anti-patterns to refuse

• Query without scorecard reference — refuse, build scorecard first
• Spray-style query ("anyone who lists Python") — push back, force precision
• No negative filters — flag, queries without NOT = noise
• Same query for all platforms — refuse, each platform needs its operator
• Outreach hook = "we have a great opportunity" — refuse, force specificity