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GonzaloTorreras

ai-dememory

Configure Review Mode

memory.review_configure_mode

Save the review mode for memory proposals in the configuration file without modifying canonical memory, supporting modes such as assisted, autonomous, balanced, batch, and strict.

Instructions

Persist the active review mode in .ai-dememory.toml without editing canonical memory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
reviewerNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
activeYes
reviewerNo
requested_modeYes
allow_apply_reviewedYes
canonical_memory_updatedYes
allow_llm_merge_proposalsYes
require_human_for_durableYes
allow_llm_false_positive_triageYes
allow_autonomous_inbox_proposalsYes
allow_llm_conflict_recommendationsYes
Behavior4/5

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

Annotations already indicate non-read-only and non-destructive behavior. The description adds meaningful context: it persists to a specific configuration file without altering canonical memory. This informs the agent about the scope of the change and what is preserved.

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?

A single sentence that efficiently conveys the core action and a key behavioral constraint. No extraneous words; every part is necessary and front-loaded.

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

Completeness3/5

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

The description covers the primary action but omits parameter details and return value expectations. However, an output schema exists (not shown), which reduces the need to describe return values. The lack of parameter semantics remains a gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must explain parameters. It does not elaborate on 'mode' (enum values) or 'reviewer' (optional string). The agent must infer meaning from names alone, which is insufficient for correct invocation.

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 the tool persists the active review mode in a specific file (.ai-dememory.toml) while highlighting it does not modify canonical memory. The verb 'persist' and the resource are specific, distinguishing it from siblings like memory.review_modes that likely only list modes.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus alternatives (e.g., memory.review_modes or other config tools). It does not mention prerequisites, side effects, or exclusions, leaving the agent to infer usage context.

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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