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GonzaloTorreras

ai-dememory

Recall Review Plan

memory.recall_review_plan
Read-only

Generate a review plan for pending recall misses, allowing you to organize review sessions without writing fixture files.

Instructions

Report pending recall miss review work without writing fixture files.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
max_age_daysNo
invalid_offsetNo
pending_offsetNo
resolved_limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitYes
staleYes
pr_urlYes
statusYes
reviewerYes
freshnessYes
next_actionsYes
fixtures_pathYes
invalid_countYes
pending_countYes
invalid_missesYes
invalid_offsetYes
pending_missesYes
pending_offsetYes
resolved_countYes
invalid_has_moreYes
pending_has_moreYes
invalid_next_offsetYes
pending_next_offsetYes
invalid_returned_countYes
pending_returned_countYes
recent_resolved_missesYes
candidate_check_commandYes
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description does not need to restate safety. It adds the behavioral detail that no fixture files are written, which is consistent. However, it does not disclose other behaviors like pagination, ordering, or what happens if no pending work exists. Minimal added value.

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 a single sentence that is front-loaded with the key action ('Report pending recall miss review work') and immediately clarifies a critical negative ('without writing fixture files'). Every word earns its place; no fluff.

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

Completeness2/5

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

Despite having an output schema and five optional parameters, the description gives no clue about the output content, pagination behavior, or when to tweak parameters. For a reporting tool with moderate complexity, this leaves significant gaps in the agent's understanding.

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

Parameters1/5

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

Schema description coverage is 0% and the tool description mentions none of the five parameters (limit, max_age_days, invalid_offset, pending_offset, resolved_limit). The agent receives no explanation of what these parameters control or how they affect results, forcing reliance on defaults and guessing.

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?

The description clearly states the tool reports pending recall miss review work and specifies it does not write fixture files, which helps distinguish from writing tools. However, among many sibling recall tools (e.g., memory.recall_miss_review, memory.recall_review_packet), it does not explicitly differentiate itself, so it falls 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 Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like memory.recall_miss_review or memory.recall_miss_candidate. There is no mention of prerequisites, context, or exclusions. The agent must infer usage from the name and purpose alone.

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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