Hermes Agent is an AI assistant that learns from its use by creating and improving skills, retaining knowledge, searching past conversations, and adapting to its users. It is for people who want to run an agent through a terminal or messaging platforms while connecting it to different AI models and scheduled tasks.
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 NousResearch/hermes-agent --skill osint-investigationgit clone --depth 1 https://github.com/NousResearch/hermes-agentWrote 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/nousresearch/hermes-agent/osint-investigation)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/osint-investigation"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-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.
<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/osint-investigation"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/osint-investigation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- NVIDIA SkillSpector pass
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 | $0.00015 | $0.02798 |
| Opus 5 | $0.00008 | $0.01399 |
| Sonnet 5 | $0.00003 | $0.00560 |
| Haiku 4.5 | $0.00002 | $0.00280 |
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 9d 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.
- `fetch_*.py` scripts use `urllib.request` and respect `Retry-After`. Heavy Copies of this mod
6 near-identical copies found in the catalogue:
- osint-investigation — 100% identical, 31 lines differ
- osint-investigation — 100% identical, 0 lines differ
- osint-investigation — 100% identical, 0 lines differ
- osint-investigation — 94% identical, 33 lines differ
- osint-investigation — 94% identical, 33 lines differ
- osint-investigation — 94% identical, 44 lines differ
How it starts
The opening of the file, as written. The whole thing — 279 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-intelskill - academic literature →
arxivskill - social-media profile discovery →
sherlockskill (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.
What ships with it
28 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.
- references/sources/courtlistener.md 3.4 KB
- references/sources/gdelt.md 3.8 KB
- references/sources/icij-offshore.md 4.3 KB
- references/sources/nyc-acris.md 3.5 KB
- references/sources/ofac-sdn.md 3.5 KB
- references/sources/opencorporates.md 3.9 KB
- references/sources/sec-edgar.md 3.1 KB
- references/sources/senate-ld.md 3.3 KB
- references/sources/usaspending.md 3.8 KB
- references/sources/wayback.md 3.1 KB
- references/sources/wikipedia.md 4.1 KB
- scripts/_http.py 2.8 KB runs code
- scripts/_normalize.py 2.0 KB runs code
- scripts/build_findings.py 7.8 KB runs code
- scripts/entity_resolution.py 6.7 KB runs code
- scripts/fetch_courtlistener.py 4.9 KB runs code
- scripts/fetch_gdelt.py 5.3 KB runs code
- scripts/fetch_icij_offshore.py 8.4 KB runs code
- scripts/fetch_nyc_acris.py 6.4 KB runs code
- scripts/fetch_ofac_sdn.py 5.4 KB runs code
- scripts/fetch_opencorporates.py 6.6 KB runs code
- scripts/fetch_sec_edgar.py 6.6 KB runs code
- scripts/fetch_senate_ld.py 4.9 KB runs code
- scripts/fetch_usaspending.py 5.4 KB runs code
- scripts/fetch_wayback.py 4.4 KB runs code
- scripts/fetch_wikipedia.py 9.2 KB runs code
- scripts/timing_analysis.py 9.0 KB runs code
- templates/source-template.md 1.2 KB
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.
- 9d ago First seen · 279 lines · 15 tokens per session scan A 1e480fc9f76a
osint-investigation is a skill published in the GitHub repository NousResearch/hermes-agent (244,603 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 2,798 once invoked, about $0.0001 per session on Opus 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 2026-09-03.
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