osint-investigation

osint-investigation is a skill for Claude Code, Codex from GGbond-bo/MemOmics-Agent. It costs 90 tokens per session (2,884 once invoked), scanned A, a copy of osint-investigation, MIT.

A framework for investigating public records across company filings, government contracts, lobbying, sanctions, court records, property records, offshore leaks, archives, and news. It links records about the same person or organization and records how strong each link is.

In plain words
What is it for?
It helps with corporate due diligence, sanctions screening, following money flows, tracing ownership, checking litigation and property records, and monitoring related news.
Why use it?
It helps compare evidence from sources that use different names and formats instead of relying on one database. It supports structured evidence chains for investigations.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps with corporate due diligence, sanctions screening, following money flows, tracing ownership, checking litigation and property records, and monitoring related news.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ggbond-bo/memomics-agent/osint-investigation
Install

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.

Any agent
npx skills add GGbond-bo/MemOmics-Agent --skill osint-investigation
Clone the repo
git clone --depth 1 https://github.com/GGbond-bo/MemOmics-Agent

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for osint-investigation

README.md
[![agentmods](https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/osint-investigation/github.svg)](https://agentmods.dev/skills/ggbond-bo/memomics-agent/osint-investigation)
Your own site
<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/osint-investigation"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/osint-investigation/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.

agentmods 80×15 button for osint-investigation

Your own site · 80×15
<a href="https://agentmods.dev/skills/ggbond-bo/memomics-agent/osint-investigation"><img src="https://agentmods.dev/badge/skills/ggbond-bo/memomics-agent/osint-investigation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,884 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 94% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00090 $0.02884
Opus 5.5 $0.00036 $0.01154
Sonnet 5.5 $0.00018 $0.00577
Haiku 4.5 $0.00009 $0.00288

Measured 2d ago against content hash c75b5a30a197, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

osint-investigation 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 2d ago.

The scan reads SKILL.md. This mod also ships 16 executable files (scripts/_http.py, scripts/_normalize.py, scripts/build_findings.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

- `fetch_*.py` scripts use `urllib.request` and respect `Retry-After`. Heavy
Origin

This is a copy

94% identical to osint-investigation — 33 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

hermes-agent/optional-skills/research/osint-investigation/SKILL.md · 278 lines

How it starts

The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OSINT Investigation — Public Records Cross-Reference

Investigative framework for public-records OSINT: government contracts, corporate filings, lobbying, sanctions, offshore leaks, property records, court records, web archives, knowledge bases, and global news. Resolve entities across heterogeneous sources, build cross-links with explicit confidence, run statistical timing tests, and produce structured evidence chains.

Python stdlib only. Zero install. Works on Linux, macOS, Windows. Most sources work with no API key (OpenCorporates has an optional free token that raises rate limits).

Adapted from the MIT-licensed ShinMegamiBoson/OpenPlanter project; expanded to cover identity / property / litigation / archives / news sources that the original didn't address.

When to use this skill

Use when the user asks for:

  • "follow the money" — government contracts, lobbying → legislation, sanctions
  • corporate due diligence — who controls company X, where are they incorporated, who serves on their boards, what filings have they made
  • sanctions screening — is entity X on OFAC SDN, ICIJ offshore leaks
  • pay-to-play investigation — contractors with offshore ties, lobbying clients winning awards
  • property ownership — find recorded deeds/mortgages by name or address (NYC; for other counties point users at the relevant recorder)
  • litigation history — find federal + state court opinions and PACER dockets
  • multi-source entity resolution where naming varies (LLC suffixes, abbreviations)
  • evidence-chain construction with explicit confidence levels
  • "what's been said about X" — international news (GDELT) + Wikipedia narrative + Wayback Machine to recover dead URLs

Do NOT use this skill for:

  • general web research → web_search / web_extract
  • domain/infrastructure OSINT → domain-intel skill
  • academic literature → arxiv skill
  • social-media profile discovery → sherlock skill (optional)
  • US federal campaign finance — FEC is intentionally NOT covered here (the API is unreliable for ad-hoc contributor-name queries on the free DEMO_KEY tier). For federal donations, point users at https://www.fec.gov/data/ directly.

Read the full file on GitHub · 278 lines

Changes

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.

  1. 2d ago First seen · 278 lines · 90 tokens per session scan A c75b5a30a197

Subscribe to this mod's changes

osint-investigation is a skill published in the GitHub repository GGbond-bo/MemOmics-Agent (30 stars, last pushed 3d ago), licensed MIT. It adds 90 tokens to every session and 2,884 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 94% identical to osint-investigation, differing in 33 lines, and is treated as a copy.

Related

Other skills, from other repositories

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens