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 human-avatar/skills-for-humanity --skill s4h-investigation-triangulationgit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-investigation-triangulation)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-investigation-triangulation"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-investigation-triangulation/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/human-avatar/skills-for-humanity/s4h-investigation-triangulation"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-investigation-triangulation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00081 | $0.01799 |
| Opus 5 | $0.00041 | $0.00899 |
| Sonnet 5 | $0.00016 | $0.00360 |
| Haiku 4.5 | $0.00008 | $0.00180 |
Grade A, and why
s4h-investigation-triangulation 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 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.
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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investigation: Triangulation
More sources does not mean better verification. If ten publications all cite the same original study, you have one data point with ten references — not ten data points. True triangulation requires genuinely independent sources: different methods, different investigators, different populations, different time periods. Convergence among truly independent sources is strong evidence. Convergence among sources that all trace back to the same origin is amplification, not corroboration. This skill teaches the difference and makes it operational.
Your Process
Step 1: State the Claim Write out the claim you want to triangulate, precisely. Vague claims are hard to triangulate because different sources may be speaking to different aspects.
Framing check: Confirm the specific claim before continuing. State what you've identified — the actual claim being triangulated and its scope — in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing of the claim and its scope]. Is that right?"
- Header: "Framing"
- Options:
- Yes — proceed — framing is correct
- Adjust — one element is off; user will correct it before you continue
- Reframe — different claim than read; incorporate the correction before proceeding
Step 2: Collect Candidate Sources List all sources that appear to speak to the claim:
- Studies, papers, reports
- Expert statements
- Data sets or statistics
- News reports or analyses
- Firsthand accounts or observations
Do not filter for independence yet — that's the next step.
Step 3: Classify Independence For each source, trace its origin and classify its independence from other sources on your list:
| Independence Level | Definition |
|---|---|
| Fully independent | Different investigators, methods, population, and time period; no data sharing or cross-referencing |
| Methodologically independent | Different methods and investigators but applied to the same data set or population |
| Structurally dependent | Cites a common primary source; draws from shared underlying data |
| Direct derivative | Is a summary, report, or commentary on another source on the list |
| Unknown | Origin cannot be traced; independence cannot be assessed |
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 · 154 lines · 81 tokens per session scan A 98b4dd7ac028
s4h-investigation-triangulation is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 1,799 once invoked, about $0.0004 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 2026-09-03.
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