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recall_memory

Search AI-captured session memories to retrieve past work details, decisions, and patterns using natural language queries.

Instructions

Search across all captured session memories using AI. Ask what you worked on, what decisions were made, or what patterns were found. Requires Memory plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language question about past sessions
toolNoFilter by AI tool (optional)
projectNoFilter by project (optional)
limitNoMax results (default 20)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Requires Memory plan,' which is a useful constraint, but doesn't describe other behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the output format looks like. For a search tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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?

The description is concise and front-loaded, starting with the core purpose. It uses three sentences efficiently: the first states the action, the second provides usage examples, and the third adds a constraint. There's no unnecessary repetition or fluff, making it easy to parse quickly.

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?

Given the tool's complexity (a search function with 4 parameters) and the lack of annotations and output schema, the description is somewhat incomplete. It covers the basic purpose and a constraint but doesn't explain return values, error handling, or how it differs from sibling tools. This leaves the agent with gaps in understanding the full context of use.

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%, meaning the input schema already documents all parameters (query, tool, project, limit) with descriptions. The description doesn't add any additional meaning or context about these parameters beyond what's in the schema. According to the rules, with high schema coverage (>80%), the baseline score is 3 even with no param info in the description.

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's purpose: 'Search across all captured session memories using AI.' It specifies the resource (session memories) and the action (search using AI), and provides examples of what can be asked. However, it doesn't explicitly differentiate from sibling tools like 'query_knowledge' or 'search_knowledge', which likely have overlapping functions.

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?

The description implies usage by stating 'Ask what you worked on, what decisions were made, or what patterns were found,' which suggests it's for querying past session content. It also mentions 'Requires Memory plan' as a prerequisite. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'query_knowledge' or 'search_knowledge', leaving the distinction unclear.

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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