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 juxt/claude-plugins --skill distillgit clone --depth 1 https://github.com/juxt/claude-pluginsWrote 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/juxt/claude-plugins/distill)<a href="https://agentmods.dev/skills/juxt/claude-plugins/distill"><img src="https://agentmods.dev/badge/skills/juxt/claude-plugins/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/juxt/claude-plugins/distill"><img src="https://agentmods.dev/badge/skills/juxt/claude-plugins/distill.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00063 | $0.07230 |
| Opus 5.5 | $0.00025 | $0.02892 |
| Sonnet 5.5 | $0.00013 | $0.01446 |
| Haiku 4.5 | $0.00006 | $0.00723 |
Grade B, and why
distill scanned grade B with 2 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 1mo 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
| `requests.post('https://slack.com/api/...')` | `Notification.created(channel: slack)` | Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| `requests.post('https://slack.com/api/...')` | `Notification.created(channel: slack)` | This is a copy
100% identical to distill — 0 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.
How it starts
The opening of the file, as written. The whole thing — 861 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Distillation guide
This guide covers extracting Allium specifications from existing codebases. The core challenge is the same as forward elicitation: finding the right level of abstraction. In elicitation you filter out implementation ideas as they arise. In distillation you filter out implementation details that already exist. Both require the same judgement about what matters at the domain level.
Code tells you how something works. A specification captures what it does and why it matters. The skill is asking "why does the stakeholder care about this?" and "could this be different while still being the same system?"
Interaction modes
This skill runs in two modes. Every instruction below that asks, prompts or validates with the user follows the mode:
- Interactive — running inline in a conversation. Ask the user directly and wait for the answer.
- Non-interactive — running as the
distillsubagent (for example inside the Allium loop), where no user is reachable. Scope the distillation from the goal you were given, and do not guess at judgement calls: record each unconfirmed judgement — intended vs accidental behaviour, actor identity, candidate processes, scope exclusions — as anopen questiondeclaration in the distilled spec, and list the parked questions in your final output.
Scoping the distillation effort
Before diving into code, establish what you are trying to specify. Not every line of code deserves a place in the spec.
Questions to ask first
-
"What subset of this codebase are we specifying?" Mono repos often contain multiple distinct systems. You may only need a spec for one service or domain. Clarify boundaries explicitly before starting.
-
"Is there code we should deliberately exclude?"
- Legacy code: features kept for backwards compatibility but not part of the core system
- Incidental code: supporting infrastructure that is not domain-level (logging, metrics, deployment)
- Deprecated paths: code scheduled for removal
- Experimental features: behind feature flags, not yet design decisions
What ships with it
1 file 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.
- 1mo ago First seen · 861 lines · 63 tokens per session scan B 5c0eb0f24c8a
distill is a skill published in the GitHub repository juxt/claude-plugins (10 stars, last pushed yesterday), licensed MIT. It adds 63 tokens to every session and 7,230 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). It is 100% identical to distill, differing in 0 lines, and is treated as a copy.
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