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330899935

hive-memory

by 330899935
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Python
Local

Propose a memory

propose

Queues a memory for human approval without altering confirmed memory. Use it to capture decisions or facts worth keeping; the entry stays pending until the human accepts it in their Hive.

Instructions

Submit a memory for the human to approve. It lands in a pending queue and changes no confirmed memory. Use it when the human says to remember something, or when a decision is reached that will still matter later. Do not use it as a scratchpad for transient reasoning or for data you merely fetched. This tool cannot confirm its own writes: the entry stays pending until the human accepts it inside their own Hive, so a success response means queued, not stored. Supply client_id to make retries idempotent.

Input Schema

NameRequiredDescriptionDefault
tagsNoFree-form tags for later filtering.
titleNoShort label shown in the human's pending queue. Helps them decide quickly.
vaultNoTarget vault name. Private vaults are rejected for cloud agents; local agents may target them.
contentYesThe memory to store, written as a standalone fact that still makes sense without this conversation - include the who and the when.
client_idNoIdempotency key. Submitting twice with the same key does not create a duplicate - use this when retrying after a timeout.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.0
    • removedInput schema / properties / vector
      Removed value: -{
-  "description": "Optional precomputed embedding stored alongside the memory, so later recalls are faster and more precise.",
-  "items": {
-    "type": "number"
-  },
-  "type": "array"
-}
  2. First observedv0.1.7

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only say non-read-only, non-destructive, closed-world; the description goes much further by explaining the queue semantics, that nothing confirmed is changed, that the write cannot be self-confirmed, and that a success response means 'queued, not stored'. It also discloses the idempotency mechanism for retries — genuinely useful context an agent could otherwise get wrong.

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

Conciseness4/5

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

Front-loaded with the action and the pending-queue consequence, then usage, then failure-mode caveat, then the parameter note. Every sentence carries distinct information, though the closing client_id sentence duplicates the schema description and is the one small piece of redundancy.

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?

With no output schema, the description carries the burden of explaining what a successful call means and does so explicitly ('success response means queued, not stored'). Combined with triggers, exclusions, and retry semantics, an agent has everything needed to call this correctly.

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 all five parameters (including content authorship guidance, vault restrictions, and client_id idempotency) are already documented in the schema. The description's only parameter reference — 'Supply client_id to make retries idempotent' — restates the schema rather than adding to it, so the baseline 3 applies.

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?

States a specific verb and resource ('Submit a memory for the human to approve') plus the crucial qualifier that it lands in a pending queue rather than confirmed memory. That distinguishes it cleanly from siblings like recall (read), say (immediate output), and manage (administration).

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?

Gives explicit positive triggers ('when the human says to remember something, or when a decision is reached that will still matter later') and explicit exclusions ('Do not use it as a scratchpad for transient reasoning or for data you merely fetched'). The when/when-not pair leaves little 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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