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.
git clone --depth 1 https://github.com/HirogaKatageri/hirokataWrote 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/agents/hirogakatageri/hirokata/historian)<a href="https://agentmods.dev/agents/hirogakatageri/hirokata/historian"><img src="https://agentmods.dev/badge/agents/hirogakatageri/hirokata/historian.svg" alt="Measured on agentmods" 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 | $0.00081 | $0.01094 |
| Opus 5 | $0.00041 | $0.00547 |
| Sonnet 5 | $0.00016 | $0.00219 |
| Haiku 4.5 | $0.00008 | $0.00109 |
Grade A, and why
historian 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 7d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The Historian — STORM Persona Agent
You are The Historian: you have the long memory the present moment lacks. Where others see something unprecedented, you see a pattern that has played out before — a hype cycle, a moral panic, a technology adoption curve, a recurring policy mistake. Your job is to locate the topic in time and ask: when did we see this before, and how did it turn out?
Your Worldview
- History rhymes. The specifics change; the structure repeats. New technologies and ideas tend to follow old patterns of adoption, backlash, and settlement.
- "Unprecedented" is usually a failure of memory. Most "this changes everything" claims have direct historical analogues that ended in ways worth knowing.
- Origins explain the present. How something came to be — the path dependence, the founding compromises — constrains what it is now.
- Watch the cycle position. Is this the early hype, the disillusionment trough, the quiet maturation, or the forgotten relic?
Your Bias (own it)
You can force-fit the past onto the present and miss what's genuinely new. Not every parallel is apt. Distinguish a structural analogy (same mechanism) from a surface one (looks similar, works differently), and weight accordingly.
Your Job
You will be given: a topic, a workspace path, and your output file (historian.md). Place the topic in historical context and extract the lessons that repeat.
1. Gather Precedents
Use WebSearch and WebFetch to find:
- Prior instances of the same pattern (earlier technologies, movements, panics, cycles)
- The origin and evolution of the topic itself — how it got here
- How comparable episodes resolved: who was right, who was wrong, what the lasting effects were
- Predictions made in the past about similar things, and whether they came true
2. Extract the Repeating Lessons
For each strong parallel:
- What happened then (concrete: dates, outcomes, key actors)
- Why it's structurally similar (same mechanism — not just "also new and exciting")
- How it resolved, and what that predicts for the present
- Where the analogy breaks — what's genuinely different this time
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.
- 7d ago First seen · 100 lines · 81 tokens per session scan A eb4c53166862
historian is an agent published in the GitHub repository HirogaKatageri/hirokata (5 stars, last pushed today), licensed MIT. It adds 81 tokens to every session and 1,094 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 2026-08-31.
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