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 skills add WingedGuardian/GENesis-AGI --skill osintgit clone --depth 1 https://github.com/WingedGuardian/GENesis-AGIWrote 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/wingedguardian/genesis-agi/osint)<a href="https://agentmods.dev/skills/wingedguardian/genesis-agi/osint"><img src="https://agentmods.dev/badge/skills/wingedguardian/genesis-agi/osint/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/wingedguardian/genesis-agi/osint"><img src="https://agentmods.dev/badge/skills/wingedguardian/genesis-agi/osint.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 213 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00020 | $0.01586 |
| Opus 5.5 | $0.00008 | $0.00634 |
| Sonnet 5.5 | $0.00004 | $0.00317 |
| Haiku 4.5 | $0.00002 | $0.00159 |
Grade A, and why
osint 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.
How it starts
The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OSINT Investigation
Purpose
Conduct open-source intelligence gathering on specific targets — people, companies, technologies, or markets. Discover publicly available information, track changes over time, assess source reliability, and produce structured intelligence reports.
This is NOT the awareness loop (which monitors Genesis's own systems). This is outward-facing investigation — finding information about external entities.
When to Use
- User requests research on a person, company, or competitive entity.
- Lead generation identifies a prospect needing deeper enrichment.
- Strategic reflection flags a competitor or technology to monitor.
- A scheduled monitoring task triggers a collection cycle.
- An inbox item references an entity worth investigating.
Investigation Pipeline
Phase 1: Target Initialization
Define the target clearly:
- Type: person | company | technology | market | competitor
- Identity: name, aliases, known associations
- Scope: what specifically to find (general profile, funding history, team composition, technology stack, competitive positioning)
- Depth: surface (headlines only) | deep (full articles + sources) | exhaustive (multi-hop research across connected entities)
Phase 2: Query Construction
Build 10-20 search queries tailored to target type:
Person:
"[name]" [company]— basic association"[name]" site:linkedin.com— public LinkedIn profile"[name]" [industry] interview OR podcast OR keynote"[name]" [company] announcement OR appointed OR promoted"[name]" github OR gitlab— technical contributions
Company:
"[company]" funding OR "series A" OR "series B" OR acquisition"[company]" hiring OR careers OR "we're hiring"site:crunchbase.com "[company]"— Crunchbase profilesite:stackshare.io "[company]"ORsite:builtwith.com "[company]"— tech stack"[company]" review OR glassdoor— employee sentiment"[company]" revenue OR valuation OR growth
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 Changed c84df657b6a8
- 1mo ago First seen · 216 lines · 20 tokens per session scan A 0b6761f1e20e
osint is a skill published in the GitHub repository WingedGuardian/GENesis-AGI (99 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 1,586 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other skills, from other repositories
search
Unified academic paper search, citation chains, paper download (arXiv LaTeX/PDF, Sci-Hub), figure extraction from papers, LaTeX source reading, BibTeX fetching, web search, and browser automation for Cloudflare-protected sites (PRL, Science, Nature, Google Scholar).
qec-construct
Verifier-in-the-loop CONSTRUCTION of quantum error-correcting codes with transversal non-Clifford gates (CCZ/T). Applies whenever the project goal is a new or better code/construction — INCLUDING search-phrased goals ("find codes beating X"), where the construct-loop (propose algebraic rule → qverify → debug) is the…
memory
Cross-project research memory. Deep-dive past projects' notes and record corrections across all Luxas research projects.
paper-figures
Extract figures from downloaded papers and include them in survey/review reports. Use when the report covers other groups' work and benefits from their architecture diagrams, experimental plots, or system schematics. Your brain prompt supplies the absolute path to the extract-figures script as {{EXTRACTFIGURES}} — use…
compute-methods
Friction sheets for field-standard computational tools and simulators (frictions, smoke tests, how to measure a saved model). Injected at spawn time.
brain-ai-memory
Save, correct and recall project facts, exact state and session handoffs through Brain-AI Memory MCP when it is connected, or set up a project-local connection when requested.