Memphora

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that 'the system will automatically identify and store relevant facts', which adds some context about automation, but doesn't cover critical aspects like whether this is a read/write operation (implied write from 'store'), permission requirements, rate limits, or what happens if extraction fails. For a tool that appears to perform memory storage with zero annotation coverage, this is inadequate.

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

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

The description is appropriately concise with two sentences that directly address purpose and automation. It's front-loaded with the core function, though the second sentence about automatic identification could be integrated more tightly. There's minimal waste, but slight room for improvement in flow.

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

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

Given no annotations, no output schema, and a tool that performs memory extraction and storage (implied mutation), the description is incomplete. It lacks details on what 'memories' entail, how they're stored, error handling, or return values. For a tool with potential side effects and no structured safety hints, this leaves significant gaps for an AI agent.

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

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

Schema description coverage is 100%, with the single parameter 'conversation' fully documented in the schema as 'List of messages in the conversation'. The description doesn't add any meaningful parameter semantics beyond what the schema provides, such as format examples or constraints on conversation length. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'extract and store' and the resource 'memories from a conversation', with the specific purpose of 'saving important information from a longer discussion'. However, it doesn't explicitly differentiate from sibling tools like memphora_store, which might also store memories but potentially from different sources.

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

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

The description implies usage context ('from a longer discussion') and suggests when to use it ('to save important information'), but doesn't provide explicit guidance on when to use this vs. alternatives like memphora_store or memphora_search, nor does it mention any exclusions or prerequisites for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.