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 HybridAIOne/hybridclaw --skill human-distillgit clone --depth 1 https://github.com/HybridAIOne/hybridclawWrote 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/hybridaione/hybridclaw/human-distill)<a href="https://agentmods.dev/skills/hybridaione/hybridclaw/human-distill"><img src="https://agentmods.dev/badge/skills/hybridaione/hybridclaw/human-distill/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/hybridaione/hybridclaw/human-distill"><img src="https://agentmods.dev/badge/skills/hybridaione/hybridclaw/human-distill.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 | $0.00085 | $0.01705 |
| Opus 5 | $0.00043 | $0.00852 |
| Sonnet 5 | $0.00017 | $0.00341 |
| Haiku 4.5 | $0.00009 | $0.00170 |
Grade A, and why
human-distill 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 11d 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Human Distillation
Turn a person's source material into a working coworker agent: a persona
written into the agent identity files (IDENTITY.md, SOUL.md, USER.md,
CV.md) and a work-module skill (skills/<alias>-playbook/) that carries
their workflows, preferences, and judgment. Every generated claim cites the
corpus documents it came from; nothing is invented beyond the source.
The deterministic engine is the hybridclaw coworker CLI. Your judgment
enters the pipeline through exactly one artefact: extraction.json. You never
edit the persona files directly — the engine renders them from validated
claims so every line stays cited, versioned, and reversible.
Hard rules
- Consent first. Distilling a real, named human requires a recorded
consent artefact. Never run
coworker consent recordon your own initiative or invent a consent statement — the operator must provide the statement and run (or explicitly dictate) the command. If a run is blocked, relay the remediation message and stop. - Evidence or nothing. Every claim in
extraction.jsonmust cite real corpus document ids from the analysis packet. If you cannot support a claim, leave it out or put the question inopenQuestions. The engine flags and drops uncited claims — do not try to route around it. - Never impersonate. The coworker mirrors the subject's judgment, not their identity. Do not sign as the subject or present generated output as written by them.
- Privacy. Third-party PII is masked at ingest. If you see unmasked
third-party contact details anywhere in generated output, stop and run
hybridclaw coworker eval --alias <alias>to surface it.
Pipeline
hybridclaw coworker distill --alias <alias> --name "<display name>" \
[--role "<role>"] [--match-alias <name|email>]... --source <path> [...]
Stages run in order, each resumable: ingest → analyse → build → merge → correct. The run record lives at runtime/distill/<run-id>/run.json in the
coworker's agent workspace, with a human-readable REPORT.md beside it.
What ships with it
4 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.
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.
- 11d ago First seen · 139 lines · 85 tokens per session scan A 072448d63c55
human-distill is a skill published in the GitHub repository HybridAIOne/hybridclaw (132 stars, last pushed today), licensed MIT. It adds 85 tokens to every session and 1,705 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 2026-08-30.
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