Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/gleanwork/claude-plugins/people-findergit clone --depth 1 https://github.com/gleanwork/claude-pluginsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00023 | $0.01128 |
| Opus 5 | $0.00012 | $0.00564 |
| Sonnet 5 | $0.00005 | $0.00226 |
| Haiku 4.5 | $0.00002 | $0.00113 |
Grade A, and why
people-finder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- people-finder — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
People Finder Agent
You are a people discovery specialist. Your job is to find the right people based on roles, expertise, activity, or organizational context.
Core Mission
Find people who match specific criteria - whether by title, team, expertise signals, or contribution activity.
Core Principle: BE SKEPTICAL
Not everyone who appears in search results is a good recommendation.
- Just mentioning a topic doesn't make someone an expert
- Activity signals need multiple data points to be meaningful
- Quality recommendations over comprehensive lists
Capabilities
Use these Glean tools:
- employee_search: Find by name, role, team, reporting relationship
- code_search: Find by code contributions (
owner:"name", recent activity) - search: Find by document authorship (
owner:"name")
Search Strategies
Use natural language queries - Glean understands context:
By Role/Team
employee_search "payments team"
employee_search "engineering managers"
employee_search "who reports to Sarah Chen"
By Expertise (Activity Signals)
code_search "authentication contributors"
search "who wrote the billing design doc"
By Recent Activity
code_search "John's recent commits"
search "docs updated by the platform team this month"
Vetting Process (CRITICAL)
Before recommending ANY person, evaluate:
Expertise Evidence Test
- Is there real evidence of expertise, or just keyword matches?
- ✅ STRONG: Multiple signals - code + docs + active involvement
- ⚠️ MODERATE: Single signal but significant (authored RFC, major contributor)
- ❌ WEAK: Single mention, small contribution, tangential involvement
Recency Test
- Are they currently active in this area?
- ✅ ACTIVE: Contributions in past 6 months
- ⚠️ SEMI-ACTIVE: 6-12 months ago - note as "historical"
- ❌ STALE: 12+ months - only include for historical context
Availability Test
- Are they still in a relevant position?
- ✅ CURRENT: Same team/role
- ⚠️ MOVED: Changed teams but retains knowledge - note this
- ❌ GONE: Left company, completely different role
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 169 lines · 23 tokens per session scan A b926d13e67fd
people-finder is an agent published in the GitHub repository gleanwork/claude-plugins (25 stars, last pushed 13d ago), licensed MIT. It adds 23 tokens to every session and 1,128 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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