Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add voxpelli/vp-claude/plugin install vp-knowledgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/voxpelli/vp-claude/people-intel)<a href="https://agentmods.dev/skills/voxpelli/vp-claude/people-intel"><img src="https://agentmods.dev/badge/skills/voxpelli/vp-claude/people-intel/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/voxpelli/vp-claude/people-intel"><img src="https://agentmods.dev/badge/skills/voxpelli/vp-claude/people-intel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00118 | $0.04749 |
| Opus 5 | $0.00059 | $0.02374 |
| Sonnet 5 | $0.00024 | $0.00950 |
| Haiku 4.5 | $0.00012 | $0.00475 |
Grade A, and why
people-intel 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 449 lines — stays where its author put it; the contents beside it link to each section on GitHub.
People Intelligence
Research a person and synthesize a structured Basic Memory person note using five enrichment sources, then cross-link existing notes.
Arguments
One argument: the person's full name. No prefix required — person names are unique identifiers in this graph.
| Form | Example |
|---|---|
<Full Name> |
Linus Torvalds |
<Full Name> |
Tim Berners-Lee |
<Full Name> |
Aaron Gustafson |
See Step 0 below for how the argument is parsed into name and descriptor.
Step 0: Normalize input
Strip leading/trailing whitespace. If the argument looks like a BM note title
(contains -), split into name and descriptor. Otherwise treat the whole
argument as the person's name.
Step 1: Check for existing note
Search by name across person notes:
search_notes(query="<name>", note_types=["person"], page_size=5)
Also do a broad text search in case the note uses a different title format:
search_notes(query="<name>", search_type="text", page_size=10)
If a matching person note is found, read it:
read_note(identifier="<title>", include_frontmatter=true, output_format="json")
Freshness check: Scope research based on note age (check updated_at):
| Note age | Sources to run | Sources to skip |
|---|---|---|
| Missing or >180 days | All 5 (full pipeline) | None |
| 60–180 days | All except Raindrop | Raindrop |
| <60 days | Tavily bio + DeepWiki only | Raindrop, Readwise |
Note any previous [controversy] observations — these guide
what to look for in new research.
Append new observations rather than overwriting.
Step 2: Five-source enrichment (run in parallel)
Multi-query strategy: For Tavily, ask 2 targeted questions (bio/role and contributions/influence) rather than one broad query.
Launch these research queries simultaneously:
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 449 lines · 118 tokens per session scan A 7e8a6c74547d
people-intel is a skill published in the GitHub repository voxpelli/vp-claude (3 stars, last pushed 14d ago), licensed MIT. It adds 118 tokens to every session and 4,749 once invoked, about $0.0006 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 2026-08-31.
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