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get_topic

Retrieve all knowledge entries for a specific topic from persistent memory for AI coding agents, including coding standards and project context.

Instructions

Retrieve all knowledge entries for a specific topic.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesTopic name to retrieve
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 states the tool retrieves entries, implying a read-only operation, but doesn't cover critical aspects like whether it returns all entries or is paginated, error conditions, or performance characteristics. This leaves significant gaps for a tool with no annotation support.

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, efficient sentence that directly states the tool's function without any wasted words. It is front-loaded with the core action and resource, making it easy to parse quickly.

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?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'knowledge entries' entail, the format of the returned data, or any behavioral traits like limitations or side effects. For a retrieval tool with no structured support, this leaves the agent under-informed.

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?

The input schema has 100% description coverage, with the 'topic' parameter fully documented in the schema. The description adds no additional semantic context beyond implying the parameter is used to filter entries by topic, which is already clear from the schema. This meets the baseline for high schema coverage.

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 action ('Retrieve') and resource ('knowledge entries for a specific topic'), making the tool's purpose understandable. However, it doesn't distinguish this tool from sibling tools like 'query_knowledge' or 'search_knowledge', which likely have overlapping functionality, so it doesn't reach the highest score.

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 such as 'query_knowledge' or 'search_knowledge'. It mentions retrieving entries 'for a specific topic', but this is part of the purpose statement rather than explicit usage instructions, leaving the agent without clear direction on tool selection.

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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