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Glama

review_memory

Destructive

Approve, edit, or reject stored memories to keep human-reviewed context accurate and rank approved entries higher in future retrieval.

Instructions

Review or edit a memory. action='approve' marks it human-reviewed; action='edit' updates content/instruction and re-embeds or clears the stale vector (this also works on already-approved memories); action='reject' soft-deletes a pending memory and is rejected for already-approved memories (use delete_memory instead). Approved memories rank higher in future injections. Writes immediately; requires agent auth when the agent has a registered key.

Input Schema

NameRequiredDescriptionDefault
actionYesAction: approve, reject, or edit
api_keyNoAPI key for agent authentication (required if agent has a registered key)
agent_idNoID of the requesting agentunknown
memory_idYesID of the memory to review
edited_contentNoNew content if action is edit
edited_instructionNoNew instruction if action is edit

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

Beyond annotations declaring destructive/non-idempotent behavior, it adds that writes happen immediately, that edit re-embeds or clears stale vectors, that approve affects future ranking, and that auth is required when the agent has a registered key. These are meaningful operational details not expressible through the annotations alone.

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?

The description is compact and front-loaded: it names the tool, then enumerates the actions and their constraints in one dense but readable passage. Every clause carries operational information.

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 multi-action mutation tool with full schema descriptions and annotations, the description covers action semantics, authorization, side effects, and the key reject/delete boundary. No output schema exists, so return-value detail is not required.

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 coverage is 100%, so baseline is 3, but the description adds real meaning by explaining what each action value does and when edit applies to already-approved memories. It does not add much for api_key or agent_id beyond the schema, so it is not a full 5.

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 states a specific verb and resource ('Review or edit a memory') and then distinguishes the three actions with precise effects. It clearly differentiates reject from delete_memory, so an agent can select it correctly against siblings like forget_memory, delete_memory, and save_memory.

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 per-action guidance: approve for human-review marking, edit for content/instruction updates, reject only for pending memories with a direct pointer to delete_memory for approved ones. This names both when to use the tool and when to use an alternative.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.