people-sourcer

Name: people-sourcer
Author: thtskaran

16stars2forks

How to install people-sourcer?

thtskaran/claude-skills/people-sourcer

$npx -y skills add thtskaran/claude-skills --skill people-sourcer

Installs into the current project.

Summary

Use this skill any time the user wants to FIND specific people online and put them in a spreadsheet — recruiting candidates, sales prospects, outreach lists, research participants, journalist sources, podcast guests, influencer lists, lead lists, beta testers, advisors, or hires.

Files · 1

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SKILL.md

1	# People Sourcer
2
3	A real recruiter, BD person, or research lead doesn't open a CRM first. They start with a question: who specifically am I trying to reach, and why? Then they hunt — across whichever platform that tribe actually lives on — and they keep notes. This skill makes Claude work that way, end-to-end, into a spreadsheet the user can act on.
4
5	## Core premise
6
7	Spam happens when you compile names without context. A list with 200 anonymous LinkedIn URLs is worse than 30 rows where each one has a real signal — this person posted last week about exactly your problem, here's how to enter their world.
8
9	So the rule is: never source from zero. Always source from signal. Find the place where the right people are already self-identifying, scrape that signal, then enrich and personalize. The personalization is what makes the difference between a useful list and noise.
10
11	## When to use this skill vs. just Google
12
13	Use this skill when the deliverable is a list of named individuals with structured fields. Don't use it for:
14	- Aggregate research ("how big is the X market") — use web search.
15	- Finding a single specific named person — just web search + verify.
16	- Company lists without people attached — that's account research.
17
18	If in doubt: if the user wants rows in a spreadsheet with names and an outreach angle, this is the skill.
19
20	## The workflow
21
22	Six phases. Each writes to a scratchpad so context survives long runs.
23
24	```
25	1. Intake → pin down WHO and WHY
26	2. Source strategy → pick platforms + queries
27	3. Discovery → iterative BrightData scraping
28	4. Enrichment → per-person profile + contact pull
29	5. Personalization → worldbuilder commentary per row
30	6. Output → multi-sheet xlsx
31	```
32
33	Skip phases that are already done. If the user hands you a list of profile URLs and just wants enrichment + commentary, jump to Phase 4.
34
35	---
36
37	## Phase 0: Scratchpad first
38
39	Before scraping anything, create a scratchpad so you don't lose the thread mid-run.
40
41	```bash
42	mkdir -p /home/claude/sourcing-work/<project-slug>/raw
43	touch /home/claude/sourcing-work/<project-slug>/brief.md
44	touch /home/claude/sourcing-work/<project-slug>/candidates.jsonl
45	```
46
47	- `brief.md` — the persona, query plan, and audience model. See `references/scratchpad-template.md`.
48	- `candidates.jsonl` — one JSON line per candidate, appended as you find them. JSONL because you'll be writing as you scrape, and a corruption in one line doesn't kill the whole file.
49	- `raw/` — raw scrapes by source URL, named like `linkedin-search-1.json`, `reddit-r-netsec-1.md`, etc.
50
51	Why JSONL for candidates: you'll likely process 30–500 people across multiple rounds. Mid-run failures shouldn't lose progress. Append-only is the right shape.
52
53	---
54
55	## Phase 1: Intake
56
57	Pin down the brief in `brief.md` before doing anything else. The single most expensive mistake in sourcing is scraping the wrong audience well.
58
59	Required:
60	- Persona — role/title, seniority, function. Be precise: "senior backend engineer with Rust experience" not "good engineer."
61	- Signals — what publicly-visible behavior identifies them? They contributed to repo X. They posted about Y last quarter. They list Z certification. They lead a meetup on W. Without signals, you're guessing.
62	- N — how many do they want? 20 ≠ 200 in workflow shape.
63	- Purpose — recruiting? sales? podcast guests? user research? This determines the "outreach angle" column entirely.
64	- Geography / language — global? specific country/city? English-only?
65	- Custom fields — anything beyond defaults the user wants captured.
66	- Output preference — xlsx (default), Google Sheet via Drive (if connected), or CSV.
67
68	If the brief is vague ("find me ML people"), ask 1–2 sharp questions before scraping. Don't ask a wall — ask the ones that actually change the search:
69	- "Are you looking to hire them, sell to them, or interview them? It changes who I prioritize."
70	- *"Any specific sig

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Type

people-sourcer

16stars2forks

View on GitHub

How to install people-sourcer?

thtskaran/claude-skills/people-sourcer

$npx -y skills add thtskaran/claude-skills --skill people-sourcer

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# People Sourcer
2
3	A real recruiter, BD person, or research lead doesn't open a CRM first. They start with a question: who specifically am I trying to reach, and why? Then they hunt — across whichever platform that tribe actually lives on — and they keep notes. This skill makes Claude work that way, end-to-end, into a spreadsheet the user can act on.
4
5	## Core premise
6
7	Spam happens when you compile names without context. A list with 200 anonymous LinkedIn URLs is worse than 30 rows where each one has a real signal — this person posted last week about exactly your problem, here's how to enter their world.
8
9	So the rule is: never source from zero. Always source from signal. Find the place where the right people are already self-identifying, scrape that signal, then enrich and personalize. The personalization is what makes the difference between a useful list and noise.
10
11	## When to use this skill vs. just Google
12
13	Use this skill when the deliverable is a list of named individuals with structured fields. Don't use it for:
14	- Aggregate research ("how big is the X market") — use web search.
15	- Finding a single specific named person — just web search + verify.
16	- Company lists without people attached — that's account research.
17
18	If in doubt: if the user wants rows in a spreadsheet with names and an outreach angle, this is the skill.
19
20	## The workflow
21
22	Six phases. Each writes to a scratchpad so context survives long runs.
23
24	```
25	1. Intake → pin down WHO and WHY
26	2. Source strategy → pick platforms + queries
27	3. Discovery → iterative BrightData scraping
28	4. Enrichment → per-person profile + contact pull
29	5. Personalization → worldbuilder commentary per row
30	6. Output → multi-sheet xlsx
31	```
32
33	Skip phases that are already done. If the user hands you a list of profile URLs and just wants enrichment + commentary, jump to Phase 4.
34
35	---
36
37	## Phase 0: Scratchpad first
38
39	Before scraping anything, create a scratchpad so you don't lose the thread mid-run.
40
41	```bash
42	mkdir -p /home/claude/sourcing-work/<project-slug>/raw
43	touch /home/claude/sourcing-work/<project-slug>/brief.md
44	touch /home/claude/sourcing-work/<project-slug>/candidates.jsonl
45	```
46
47	- `brief.md` — the persona, query plan, and audience model. See `references/scratchpad-template.md`.
48	- `candidates.jsonl` — one JSON line per candidate, appended as you find them. JSONL because you'll be writing as you scrape, and a corruption in one line doesn't kill the whole file.
49	- `raw/` — raw scrapes by source URL, named like `linkedin-search-1.json`, `reddit-r-netsec-1.md`, etc.
50
51	Why JSONL for candidates: you'll likely process 30–500 people across multiple rounds. Mid-run failures shouldn't lose progress. Append-only is the right shape.
52
53	---
54
55	## Phase 1: Intake
56
57	Pin down the brief in `brief.md` before doing anything else. The single most expensive mistake in sourcing is scraping the wrong audience well.
58
59	Required:
60	- Persona — role/title, seniority, function. Be precise: "senior backend engineer with Rust experience" not "good engineer."
61	- Signals — what publicly-visible behavior identifies them? They contributed to repo X. They posted about Y last quarter. They list Z certification. They lead a meetup on W. Without signals, you're guessing.
62	- N — how many do they want? 20 ≠ 200 in workflow shape.
63	- Purpose — recruiting? sales? podcast guests? user research? This determines the "outreach angle" column entirely.
64	- Geography / language — global? specific country/city? English-only?
65	- Custom fields — anything beyond defaults the user wants captured.
66	- Output preference — xlsx (default), Google Sheet via Drive (if connected), or CSV.
67
68	If the brief is vague ("find me ML people"), ask 1–2 sharp questions before scraping. Don't ask a wall — ask the ones that actually change the search:
69	- "Are you looking to hire them, sell to them, or interview them? It changes who I prioritize."
70	- *"Any specific sig

People who liked this also viewed

6 picks

Type