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Write Studocu Agent Memory

write-memory
Destructive

Upsert one durable memory document per (scope, kind) for the authenticated user. Provide project_id for project-local memory, or null/omit for global. Identity comes from Core via the session bearer, not from input.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesMemory kind, e.g. study_preference or project_learning_context.
valueYesFreeform memory document. MVP convention is { content: string }.
project_idNoProject UUID for project-local memory; null or omitted stores global (user-level) memory.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesMemory kind that was written.
valueYesStored memory document.
userIdYesOwner of the memory document.
createdAtYesCreation timestamp of the row.
projectIdYesOwning project UUID, or null for global memory.
updatedAtYesLast write timestamp of the row.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true and openWorldHint=false, so the safety profile is covered. The description adds real context beyond that: the upsert is keyed one-document-per-(scope, kind) (implying replacement of prior content) and identity is derived from the session bearer rather than input. It does not explicitly state that existing content is overwritten or what errors occur.

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?

Two sentences, zero waste, with the core upsert/keying semantics front-loaded before the scope-selection detail. Every clause earns its place.

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?

An output schema exists, so return values need not be explained, and the description covers scope, keying, and auth identity for a mutation tool. It leaves out what happens to previously stored content on overwrite and whether 'kind' is an open or constrained vocabulary, which keeps it from a 5.

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 kind, value, and project_id are already fully documented in the schema; the description largely restates the project_id null/omit behavior. The one added nuance is that identity is not a parameter but comes from the session bearer. Baseline 3 is appropriate.

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

Purpose4/5

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

States a specific verb (upsert) and resource (durable memory document) with the keying semantics '(scope, kind) per authenticated user', which distinguishes it from read-memory and delete-memory. It does not explicitly name a sibling or say what it is not, so it stops short of a 5.

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

Usage Guidelines3/5

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

Gives a clear condition for choosing project-local vs global storage via project_id, which is genuine usage guidance. However, it never says when to prefer this tool over siblings like write-artifact or get-context, and gives no prerequisites or exclusion cases, so guidance is implied rather than explicit.

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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