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

With no annotations provided, the description takes on full responsibility for behavioral disclosure. It clearly explains that by default the text is stored verbatim with no LLM call (offline, free), and that setting infer=true triggers LLM fact extraction. This goes beyond the schema by adding cost/offline context and a requirement. It does not mention return values or side effects, but the key behavioral traits are covered.

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 two sentences, each earning its place. The first states the core purpose, and the second explains the default vs. infer behavior. It is front-loaded with the primary action and contains zero fluff, making it exemplary in conciseness.

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 the moderate complexity (5 parameters, no annotations, no output schema), the description covers the main action, default behavior, and a key option (infer) with its prerequisite. It does not explicitly state the return value, which would be helpful since there is no output schema, but the description is sufficiently complete for an agent to understand when and how to invoke the tool.

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?

The schema already covers 100% of parameters with meaningful descriptions, so a baseline of 3 applies. The description adds some context around the infer parameter (offline/free, requires configured LLM) but does not enrich the semantics of user_id, agent_id, or metadata beyond their schema descriptions. Overall, the added value is moderate.

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 opens with a clear verb+resource statement: 'Store a memory in the local OSS Mem0 store.' This immediately distinguishes it from sibling tools like search_memories, get_memories, update_memory, and delete_memory, establishing it as the creation tool. It also adds specificity about the default verbatim storage behavior, deepening the clarity.

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 provides explicit context for use: it is for storing a memory, with a clear distinction between the default offline/free mode and the LLM-based infer mode. It states a key prerequisite ('requires a configured LLM') for the infer option. However, it does not explicitly mention alternatives or when not to use the tool, so it lacks exclusions.

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

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

No annotations are provided, so the description must carry the full burden for behavioral disclosure. It states the destructive action ('Delete all memories') but does not warn about permanence, irreversibility, or clarify the ambiguous 'and/or' scoping semantics (whether both scopes are AND or OR). This is a significant gap for a bulk delete operation.

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 two sentences, front-loaded with the action, and contains no filler. Every word contributes meaning, making it highly efficient.

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?

For a simple bulk delete tool with two well-documented parameters and no output schema, the description covers the core essentials. However, it leaves out safety-related context (e.g., that deletion is permanent) and the precise scoping logic, which are important for a destructive operation. The absence of annotations elevates the need for such details.

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 coverage is 100%, so the baseline is 3. The description adds value by specifying that at least one scope is required, a constraint not captured in the schema's 'required' array. It also clarifies that user_id and agent_id serve as scope filters, though the 'and/or' relationship could be more explicit.

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 uses a specific verb 'Delete' and resource 'all memories for a user and/or agent', clearly distinguishing it from the sibling 'delete_memory' by the 'all' qualifier. It also adds the scope requirement, making the tool's purpose unambiguous.

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 provides an important usage constraint ('At least one scope is required') but does not explicitly state when to use this tool versus alternatives like delete_memory. The intended use case (bulk deletion) is implied rather than stated.

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

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

With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It only restates the action and does not mention permanence, side effects, error handling, or required permissions. This is a destructive operation, so more transparency about irreversibility would be expected.

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 a single, front-loaded sentence with zero filler. Every word earns its place, making it highly concise and well-structured.

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?

For a simple single-parameter delete tool, the description is nearly complete. It covers what and how, and the schema handles the parameter. However, it could note permanence or mention that delete_all_memories exists for bulk deletion, though not strictly necessary given the simplicity.

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%, so the baseline is 3. The description adds 'by ID', which reinforces the memory_id parameter but does not provide additional details like format, uniqueness, or where the ID comes from.

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 action ('Delete') and the resource ('a single memory') with a specific method ('by ID'). It distinguishes from sibling tool delete_all_memories by explicitly saying 'single', making the purpose unambiguous.

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?

Usage is implied: this is for deleting one memory, not all. However, there is no explicit guidance on when to choose this over delete_all_memories or other sibling tools, nor any exclusions or prerequisites.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It reveals ordering and filter options but does not state return format, pagination, default behavior beyond the schema, or explicitly confirm it is read-only. The word 'List' implies non-mutating behavior, but additional detail would be helpful.

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 a single, well-structured sentence that front-loads the core purpose ('List stored memories') and immediately specifies ordering and filters. No unnecessary words or repetition.

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?

For a simple list tool with zero required parameters and a fully described schema, the description sufficiently covers the primary behavior, ordering, and filtering options. An output schema is absent, but the description's clarity allows an agent to understand what the tool does. It could mention default top_k behavior, but the schema already covers that.

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?

The input schema fully describes all three parameters with 100% coverage, so the baseline is 3. The description adds a general reference to 'optional user/agent filters' but does not add meaning beyond the schema's parameter descriptions.

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 tool's verb ('List') and resource ('stored memories'), and specifies ordering ('newest first'). It also indicates optional filters, which distinguishes it from siblings like search_memories and get_memory.

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 when to use the tool—listing memories with optional user/agent filters—but does not explicitly differentiate it from search_memories or state when not to use it. No alternative tools are mentioned.

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

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

With no annotations, the description carries the burden of disclosing behavior. It only states the basic read operation, but does not mention what happens on not-found (error, null), return format, or any other behavioral details. The description adds little beyond the tool's name.

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 a single concise sentence with no filler. It is front-loaded with the key action and directly states the tool's purpose.

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 the tool's simplicity and lack of output schema, the description is still incomplete because it does not specify the return value, error behavior, or any caveats. For a retrieval tool, these are critical expectations that the description should address.

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%, so the parameter is already well documented in the schema ('Memory ID returned by add/search/list.'). The description does not need to add parameter info, so baseline 3 is appropriate.

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 uses a specific verb ('Retrieve') and resource ('a single memory') with a clear method ('by its ID'), which fully distinguishes it from sibling tools like get_memories (plural), search_memories, and add_memory.

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 (when you have a memory ID), but it does not explicitly state when to prefer this over alternatives like get_memories or search_memories, nor does it mention exclusions. No explicit guidance is provided.

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

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

No annotations are provided, so the description carries the full burden. It mentions 'local embeddings' as a behavioral trait, but omits whether the operation is read-only, how similarity scores are computed, or what the return format looks like.

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 two sentences with no redundant or irrelevant information. It is front-loaded with the core purpose and then adds the local embedding detail.

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?

With no output schema and five parameters, the description leaves gaps. It does not explain the return value, the meaning of the similarity score, or how filtering by user/agent interacts with the search. More detail is needed for full context.

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%, and each parameter is already well-documented. The description adds no extra meaning to the parameters, so the baseline score of 3 is appropriate.

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 tool searches memories using semantic similarity, with a specific verb and resource. It distinguishes from siblings like get_memories, which likely perform exact retrieval.

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?

Usage is implied through the 'semantic similarity' phrasing, suggesting use when similarity-based search is needed. However, no explicit guidance is given on when to prefer this over get_memories or other alternatives.

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

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

With no annotations, the description carries full responsibility for behavioral disclosure. 'Overwrite' hints at destructive action, but it does not clarify whether metadata is fully replaced when provided, what happens if metadata is omitted, whether the memory must exist, error behavior, or return values.

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 a single concise sentence that immediately states the action and target. No wasted words.

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?

Even though the schema describes parameters well, the description lacks important context for a mutation tool: metadata replacement semantics, behavior on nonexistent ID, output expectations, and any permissions/limitations. This is incomplete for an agent to use confidently.

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?

The schema has 100% parameter coverage, so a baseline of 3 is appropriate. The description adds minimal semantic value beyond the schema, though it does note that metadata is optional.

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 uses the specific verb 'overwrite' and identifies the resource ('a memory by ID'), which clearly distinguishes it from sibling tools like add_memory, get_memory, and delete_memory.

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 usage context is implied: overwriting suggests modifying an existing memory. However, there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.

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