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distill

Automatically convert completed work and active decisions into knowledge memories by reading from agentsync and context-keeper, eliminating manual export and copy-paste.

Instructions

Automatically turn work that already happened into knowledge. Reads two substrates natively — no export step, no copy-paste:

  1. agentsync: every DONE claim on the coordination branch (task + partner note + changed files) becomes an 'outcome' memory. The note your partner left for reconciliation is exactly the knowledge worth keeping.

  2. context-keeper: every active decision and constraint in .context/ becomes a memory with its rationale, preserving the dec-NNN/con-NNN provenance.

Idempotent — each source record imports at most once; re-run freely (e.g. from a session-end or post-commit hook for passive capture).

Release-time capture (opt-in, CAMBIUM_RELEASE_CAPTURE=1): agentsync erases a claim from live state the moment it is released or re-claimed, so a claim that completes and churns before the next full distill is lost. With the flag on, distill also remembers the last-seen claim per agent and captures any that has churned away since the previous run — from that snapshot, via the same watermark, so nothing double-imports. Wire distill to fire on completion events and captured-once-at-completion is the result. The residual gap: a done state that lives and dies entirely between two runs is never observed (only the agentsync git log holds it).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It thoroughly discloses idempotent behavior, the release-time capture mechanism, and a residual gap where work might be lost. This level of transparency is exceptional.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is quite long and packed with information, but it could be more concise. It uses paragraph structure rather than bullet points, which trades some clarity for detail. Still, every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters and an output schema exists, the description covers behavior, limitations, use cases, and mechanisms thoroughly. It is complete and leaves little ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and schema coverage is 100% trivially. The description does not need to add parameter information, and it provides extensive context beyond parameter semantics. Baseline for 0 params is 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that distill turns completed work into knowledge, detailing two specific native substrates (agentsync and context-keeper). It distinguishes itself from sibling tools by focusing on automated capture from already completed tasks, unlike capture or generalize.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use the tool (re-run freely, from session-end or post-commit hook) and explains the opt-in release-time capture. It does not explicitly state when not to use, but the context implies it's for automated knowledge capture, and the residual gap is noted.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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