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H1an1

mem-universe

by H1an1

write

Create and index memory entries in a shared knowledge base, organized into shared or personal layers with author provenance.

Instructions

Write a memory file (also indexes it). Returns {ok, path}.

There are exactly two layers. `path` is store-relative and starts with one:
  - `shared/...`    — the cross-agent knowledge base (skills/tools/lessons/rules)
  - `personal/...`  — the owner's personal space (free-form)

`layer` is OPTIONAL — leave it out and it's inferred from the path. If you do
pass it, the only valid keys are "shared" and "personal".

Layers are SHARED spaces, not per-author: every connected agent reads and
writes the same paths. `author_agent` only records who wrote an entry
(provenance); it does not partition or hide anything. So `personal/` is "the
owner's personal layer", visible to all connected agents — NOT "this agent's
private space". Truly secret material should not be put in this store at all.

`type` is one of skill|tool|lesson|rule|conversation|note (inferred from the
path if omitted). An explicit type="skill" must include the 5 template
sections, each headed in Chinese OR English: 目标/Goal, 何时用/When to use,
前置/Preconditions, 步骤/Steps, 验证/Verify.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
tagsNo
typeNo
layerNo
reasonNo
sourceNo
contentYes
author_agentYes
Behavior5/5

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

With no annotations, the description fully discloses indexing behavior, shared space semantics, type constraints for skills, and privacy warnings. All behavioral traits are clearly explained.

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?

Every sentence adds value; structured logically from core purpose to layer explanation to parameter details. No wasted words.

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

Completeness4/5

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

Comprehensive for 8 parameters with no output schema. Explains return value, layer inference, type requirements, and sharing model. Minor gaps in tags/reason/source descriptions, but these are optional.

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?

Despite 0% schema coverage, the description adds meaning for path, layer, type, author_agent, and content. Tags, reason, and source are not described but are optional. Compensates well.

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 'Write a memory file (also indexes it). Returns {ok, path}.' This specifies the action and resource, directly distinguishing from siblings like delete, read, and list.

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?

Explains the two layers (shared/personal) and when each is appropriate, and notes that author_agent is for provenance only. However, does not explicitly contrast with other tools or state when to avoid using it.

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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