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lna-lab

distill-kura

by lna-lab

kura_map

Lists every memory's one-line trigger in the current kura, giving an overview of what exists. Use it to check if a topic was discussed or pick which memory to open.

Instructions

Show the whole index of the kura — every memory's one-line recognition trigger, in one answer. Use it when you need to see WHAT EXISTS rather than look something up: before claiming a topic was never discussed, when choosing which memory to open, or right after switching kura. It is a map, not the contents: open a memory with kura_read for the detail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
storeNoWhich kura. Omit for the current one.
Behavior4/5

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

No annotations are present, so the description carries the full burden. It clearly frames a display operation ('Show the whole index... in one answer') and sets output expectations ('map, not the contents'). It does not discuss permissions or exact formatting, but for a non-mutating index tool the core behavioral disclosure is present.

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

Conciseness5/5

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

Three sentences, each earning its place: the first states the action and scope, the second gives concrete use cases, and the third clarifies depth and names the sibling for details. It is front-loaded and free of filler.

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?

For a low-complexity tool with one optional parameter and no output schema, the description provides the essential context: what it returns, when to use it, what it is not, and where to go for detail. Nothing needed to call it correctly is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so the single 'store' parameter is already documented as 'Which kura. Omit for the current one.' The description adds no parameter-level detail beyond that, so it meets the baseline but does not exceed it.

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 opens with a specific verb and resource: 'Show the whole index of the kura - every memory's one-line recognition trigger.' It also distinguishes itself from siblings by saying it is 'a map, not the contents' and explicitly directs details to kura_read, so an agent can tell it apart from the other tools.

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

Usage Guidelines5/5

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

It gives explicit when-to-use conditions ('when you need to see WHAT EXISTS... before claiming a topic was never discussed, when choosing which memory to open, or right after switching kura') and an explicit alternative ('open a memory with kura_read for the detail'). This is clear routing guidance rather than leaving usage to inference.

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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