Borrowing it
Nothing to install: this file belongs to Neetx/ai-security-research-radar. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Neetx/ai-security-research-radar/main/.claude/skills/radar-source-verify/SKILL.mdgit clone --depth 1 https://github.com/Neetx/ai-security-research-radarWrote 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/neetx/ai-security-research-radar/radar-source-verify)<a href="https://agentmods.dev/skills/neetx/ai-security-research-radar/radar-source-verify"><img src="https://agentmods.dev/badge/skills/neetx/ai-security-research-radar/radar-source-verify/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/neetx/ai-security-research-radar/radar-source-verify"><img src="https://agentmods.dev/badge/skills/neetx/ai-security-research-radar/radar-source-verify.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 | $0.00075 | $0.00877 |
| Opus 5.5 | $0.00030 | $0.00351 |
| Sonnet 5.5 | $0.00015 | $0.00175 |
| Haiku 4.5 | $0.00007 | $0.00088 |
Grade A, and why
radar-source-verify scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- arXiv: `curl -sL 'https://export.arxiv.org/api/query?id_list=ID1,ID2'` The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 5d ago Changed · +1 tokens per session aebf86a88ccf
- 1mo ago First seen · 59 lines · 74 tokens per session scan A 1a05d0fc7a85
radar-source-verify is a skill published in the GitHub repository Neetx/ai-security-research-radar (7 stars, last pushed yesterday), with no licence file. It adds 75 tokens to every session and 877 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
plur-create-engrams
Create or improve PLUR engrams from conversations, documents, decisions, observations, and explicit preferences. Use for memory extraction, engram authoring, or reviewing proposed memories, including global, scoped, pinned, retrieved, and provisional knowledge. Ordinary use of existing memories does not require this…
Effective Memory
The essential habits for an AI agent with memory — session bookends, learning triggers, verification, safety, and the operational discipline that turns raw recall into compounding intelligence. Keyword-matched after installation.
recall
Recall this repository's OwnMem local memory before changing code, and keep it healthy. Use when a repository contains .ownmem/, when past debugging lessons could apply ("have we hit this before", "why is it done this way"), or when the user mentions ownmem, project memory, or recalling across sessions.
init
Install or update OwnMem in the current repository. Use when the user asks to set up OwnMem, add local project memory for coding agents, or refresh an existing OwnMem installation after a version bump.
honcho-integration
Integrate Honcho memory into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, and accessing Honcho's representation.
honcho-memory
Use Honcho as your persistent memory of the user. Apply at the start of every conversation (recall what Honcho knows), whenever personalization or past context would help, when the user asks what you remember or know about them, and after every exchange (record the turn). Works the same in Cursor and in Grok Bot.