distill

A method for deriving a software specification from an existing codebase. A specification describes what a system should do and why, without tying it to a particular programming language or internal design.

In plain words
What is it for?
It is for reverse-engineering requirements, documenting existing behaviour, and creating an Allium specification from source code.
Why use it?
It turns working code into a clearer description of its observable behaviour, while separating important domain rules from implementation details. Uncertain interpretations are recorded as questions instead of being guessed.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/juxt/allium/distill
Any agent
npx skills add juxt/allium --skill distill
Clone the repo
git clone --depth 1 https://github.com/juxt/allium

Made for: Claude Code, Codex.

Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,230 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00063 $0.07230
Opus 5 $0.00032 $0.03615
Sonnet 5 $0.00013 $0.01446
Haiku 4.5 $0.00006 $0.00723

Measured 2d ago against content hash 5c0eb0f24c8a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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 2d 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)` |
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

  • distill — 100% identical, 0 lines differ
skills/distill/SKILL.md · 861 lines

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 distill subagent (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 an open question declaration 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

  1. "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.

  2. "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

Read the full file on GitHub · 861 lines

Files

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.

Changes

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.

  1. 2d ago First seen · 861 lines · 63 tokens per session scan B 5c0eb0f24c8a

Subscribe to this mod's changes

distill is a skill published in the GitHub repository juxt/allium (478 stars, last pushed 6d ago), licensed MIT. It adds 63 tokens to every session and 7,230 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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