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gardener_request

Submit a plain-language request to reorganize memory; returns reviewable pending proposals for folding duplicates, retiring stale entries, synthesizing notes, moving items, or reclassifying kinds.

Instructions

The natural-language entry point for REORGANIZING memory. Describe the change in plain language and it returns reviewable pending proposals -- fold duplicates together ("these two memories are duplicates -- keep the newer"), retire stale memories ("archive anything about the old port 8080"), synthesize several into one ("combine the three auth-flow notes"), move a mis-filed memory to another EXISTING project ("the iOS DFU memory belongs in arctop-ios"), or reclassify a memory's kind ("the wordmark memory is a convention, not a constraint"). Use this whenever the user describes how they want their knowledge organized; if the intended change is ambiguous, ask them a clarifying question first. It NEVER mutates memories: it only creates pending proposals -- review with gardener_proposals, resolve with gardener_apply. If the request is to split one project into NEW child projects, it recognizes that and returns guidance (splitSource) pointing you at gardener_split instead. Needs an LLM chat client.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNoscope candidate memories: a project slug (its memories + globals), "global" for globals only, or "all" for every project on the machine. Omit to use the session's project.
requestYesthe reorganization request in plain language
Behavior5/5

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

Explicitly states 'It NEVER mutates memories: it only creates pending proposals', which adds crucial context beyond annotations (readOnlyHint=false). Also mentions returning guidance for split operations.

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?

Description is well-structured with purpose upfront, followed by examples and usage notes. Slightly lengthy but each sentence adds value; could be more concise without losing meaning.

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's complexity (natural language processing, proposal creation), the description covers input, output (pending proposals), workflow (review with gardener_proposals, apply with gardener_apply), and special cases (split guidance). No output schema, but return behavior is adequately described.

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?

Schema descriptions are already comprehensive (100% coverage). Description adds value by giving examples of what the 'request' parameter should contain (e.g., 'fold duplicates', 'retire stale'), illustrating the plain language format.

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?

Description clearly defines the tool as the natural-language entry point for reorganizing memory, listing concrete examples like folding duplicates, retiring stale, and moving memories. It distinguishes from sibling tools like gardener_apply, gardener_proposals, and gardener_split.

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?

Explicitly states when to use ('whenever the user describes how they want their knowledge organized') and when not to (if ambiguous, ask clarifying question; if splitting into new child projects, use gardener_split). Also notes the workflow after creating proposals.

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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