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workers_memory_add

Add a memory entry to a topic to retain context and enable AI assistants to recall information across conversations.

Instructions

Add a memory entry to a topic (topic_*).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNo
contentYes
group_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic operation—adding a memory entry—but omits critical behaviors: whether it appends or overwrites existing entries, what happens if the topic is missing, any permission requirements, rate limits, or side effects. The existence of an output schema is not mentioned, so agents lack insight into the return value.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise and front-loaded with the verb. However, it is too sparse for the tool's complexity (3 parameters, no annotations). It could include more context (e.g., parameter roles, return value) without becoming overly long. It earns its place for stating purpose but leaves significant gaps.

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 tool's 3 parameters, 0% schema coverage, and no annotations, the description is insufficiently complete. It does not explain the relationship to sibling tools (e.g., that workers_memory_create_topic creates topics first), what the output schema contains, or how group_id and topic interact. An agent would lack the full context needed to use this tool correctly, especially within the broader memory system.

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?

Schema description coverage is 0%, yet the description only indirectly explains one parameter ('topic' via 'to a topic'). The required 'content' parameter is not explained at all—what type of data it should contain (text, JSON, etc.). The optional 'group_id' is completely unexplained. The description adds little meaning beyond the bare schema, failing to compensate for the lack of schema descriptions.

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 ('Add a memory entry') and the resource ('to a topic'), with the hint '(topic_*)' indicating topic naming convention. It distinguishes itself from sibling tools like workers_memory_get, workers_memory_edit, and workers_memory_delete by using a different verb ('add' vs 'get/edit/delete'). However, it lacks specificity about what constitutes a 'memory entry' beyond the content parameter.

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?

No guidance is provided on when to use this tool versus alternatives like workers_memory_create_topic (if topic doesn't exist) or workers_memory_edit (to modify existing entries). There is no mention of prerequisites, such as whether the topic must already exist, or conditions that would make this tool inappropriate. The description is silent on 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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