mem0-mcp-selfhosted

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools are clearly distinct (add_memory vs get_memory vs delete_memory, etc.). However, delete_entities and delete_all_memories are noted as functionally equivalent in self-hosted mode, causing some overlap. Also, mcp_get_entity and mcp_search_graph could be confused for entity lookups.
Naming Consistency3/5
Many tools follow verb_noun pattern (add_memory, get_memory, delete_memory), but some use noun_first (memory_history, memory_queue_status) and two are prefixed with 'mcp_' (mcp_get_entity, mcp_search_graph), breaking consistency. Overall readable but mixed.
Tool Count5/5
15 tools is well-scoped for a memory server. It covers CRUD, search, history, async task management, entity operations, and document ingestion without excess.
Completeness4/5
Core memory operations are fully covered (add, get, update, delete, search, history). Entity management and async task monitoring are included. Minor gap: no task cancellation tool. Also, delete_entities is redundant with delete_all_memories.
Average 3.8/5 across 15 of 15 tools scored. Lowest: 3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 13 commits in the last 12 weeks
- Last stable release on August 2, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description only says 'fetch', implying read-only but omitting behaviors like error handling, return format, or rate limits.
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?
Very concise single sentence, but it lacks necessary context; conciseness is achieved at the expense of completeness.
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?
Despite simple tool (1 parameter, output schema exists), description misses usage context and behavioral details, making it incomplete for effective agent 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 coverage is 100% with description 'Exact memory UUID to fetch'; description adds 'by its ID' but that's redundant, not adding value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'fetch', resource 'a single memory', and method 'by its ID', distinguishing it from siblings like get_memories and search_memories.
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 on when to use this tool versus alternatives like search_memories or when not to use it; usage is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only says 'semantic search,' failing to note that it is read-only, does not modify state, or indicate any performance characteristics. The agent cannot infer safe usage from this description alone.
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 a single, concise sentence that immediately conveys the tool's function. While it could benefit from more detail, it is front-loaded and contains no unnecessary words.
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 14 parameters and an output schema, the description lacks essential context. It does not summarize key capabilities like filtering by domain, user, or importance, nor does it explain the search behavior (e.g., returns ranked results). The agent would need to rely entirely on the schema for guidance.
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 coverage is 100%, so every parameter is already described in the schema. The description adds no new semantic value beyond what the parameter descriptions already provide, meriting the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a semantic search tool over existing memories. This directly communicates its function and distinguishes it from sibling tools like add_memory (creation) or get_memories (retrieval of all memories).
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 about when to use this tool versus alternatives. It does not explain when other sibling tools like get_memories or mcp_search_graph would be more appropriate, nor does it mention any prerequisites or conditions for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides some behavioral context: it uses server-side aggregation with fallback for older versions. However, it doesn't disclose read-only nature, performance implications, or what 'holds memories' entails.
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 (two sentences) and front-loads the primary purpose. The technical detail about Qdrant is somewhat jargon-heavy but not excessive. No wasted sentences.
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 no parameters and an output schema exists, the description is adequate but lacks context about what 'holds memories' means, the scope of the list, or any constraints. It could be more complete for a tool with many siblings.
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 schema has no parameters and 100% coverage trivially, so baseline is 3. The description adds no parameter information beyond the schema, which is acceptable since there are no parameters.
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 lists which users/agents/runs hold memories. It uses a specific verb and resource, but doesn't explicitly differentiate from sibling list tools like get_memories or search_memories.
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 on when to use this tool versus alternatives. The description mentions implementation details (Qdrant API) but doesn't help the agent decide when to invoke list_entities over other list/search tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only states the destructive action. No details on permissions, reversibility, or side effects are provided.
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?
Extremely concise at 4 words, front-loaded with the action, and no wasted text. Appropriate for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward delete tool with one parameter and an output schema, the description covers the basic purpose. However, it lacks any additional context such as requirements or limitations.
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 coverage is 100% for the single parameter, but the description adds no extra meaning beyond the schema's 'Exact memory UUID to delete.' Baseline 3 is appropriate as the description does not enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Delete a single memory' uses a specific verb and resource, clearly distinguishing from sibling tools like delete_all_memories.
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 on when to use this tool versus alternatives such as delete_all_memories or delete_entities. The description lacks context for usage decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions 'substring matching' but omits critical details like case sensitivity, scope of search (e.g., nodes/relationships), and whether the tool is read-only. This leaves the agent uncertain about behavior.
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 sentence with no redundant words. It is front-loaded and efficient, earning its place with specific verb and resource.
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?
The tool is simple (one parameter, output schema exists), but the description does not clarify the substring matching behavior or what entity types are searched. The output schema exists but the agent might benefit from knowing the matching semantics. Overall adequate but has gaps.
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 coverage is 100% for the single parameter 'query', and the description adds minimal extra meaning beyond the schema's description. It does not provide format, length limits, or examples beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches entities by name/id substring matching in a Neo4j knowledge graph. It uses a specific verb ('search') and resource ('entities'), and distinguishes from siblings like 'search_memories' (searches memories) and 'mcp_get_entity' (likely gets a specific entity).
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 provides no explicit when-to-use or when-not-to-use guidance. It neither mentions alternatives nor exclusions. Usage is implied (searching entities), but no differentiation from similar tools like 'list_entities' or 'search_memories' is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses cascade-deletion behavior, but does not mention irreversibility, required permissions, or error states. The description is adequate but not rich.
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?
Two concise sentences with no fluff. The first states the core action, the second provides helpful context. Every sentence earns its place.
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?
The description and schema together cover the basic delete behavior, but they do not specify that exactly one entity identifier must be provided. Given the absence of required parameters, this is a notable gap. An output schema exists but its contents are not visible.
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 coverage is 100%, so the schema already describes each parameter. The description adds 'cascade-delete all its memories' but this is implicitly clear from the schema. No additional semantic value beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'delete' and resource 'entity', and specifies cascade-deletion of memories. It also distinguishes itself by noting functional equivalence to delete_all_memories, differentiating from sibling tools that delete single memories.
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 mentions equivalence to delete_all_memories but does not explicitly guide when to use this tool versus alternatives like delete_memory or delete_all_memories. It lacks explicit when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It implies a read operation but does not disclose pagination mechanics, ordering, rate limits, or any side effects. The behavioral disclosure is minimal.
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?
A single 8-word sentence that is front-loaded and contains no wasted words, perfectly concise.
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?
Output schema exists, so return values are covered. The description addresses the core purpose but omits details like pagination requiring multiple calls, default limits, or sorting. It is minimally complete.
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%, so the schema already documents all parameters. The description adds only the high-level hint 'using filters', providing no extra meaning. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Page through memories using filters instead of search' clearly specifies the verb ('page through'), resource ('memories'), and contrasts with the sibling tool 'search_memories', 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.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states 'instead of search', guiding the agent to use this tool when filtering rather than full-text searching. It gives clear context but does not explicitly list when not to use or describe prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions 'bidirectional', which is useful, but does not clarify if the operation is read-only, requires authentication, has limits, or how the result is structured. Basic transparency but incomplete.
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 a single sentence that is front-loaded and purposeful. While very concise, it could be slightly expanded with minimal additional detail without sacrificing structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (from context signals), the description does not need to detail return values. For a one-parameter tool with simple behavior, the description adequately covers the functionality, though some users might want more detail about the bidirectional aspect.
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 coverage is 100%, and the schema already describes the 'name' parameter as 'Exact entity name to look up.' The description adds no additional semantic value beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get all relationships for a specific entity (bidirectional).' It uses a specific verb ('Get') and resource ('relationships for a specific entity'), and highlights bidirectional behavior, distinguishing it from sibling tools like mcp_search_graph.
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 when needing all relationships of an entity, but does not explicitly state when to use this tool versus alternatives (e.g., mcp_search_graph) or provide exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool does not call raw delete_all but uses a safe bulk-delete, implying safety. However, it omits details on destructiveness, reversibility, or auth needs, which are important for a deletion tool.
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 highly concise: two sentences that front-load the purpose and key constraint (requires filter). Every sentence earns its place with no redundancy.
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?
While the description covers purpose and filter requirement, it lacks return value information. There is no output schema to compensate, so the agent is left guessing about what the tool returns (e.g., count, confirmation). For a bulk deletion tool, this is a notable gap.
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 coverage is 100% with clear descriptions for each parameter (run_id, user_id, agent_id). The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Bulk-delete') and resource ('all memories in the given scope'). It distinguishes from siblings like 'delete_memory' by specifying bulk operation and requiring a filter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Requires at least one filter,' providing clear usage context. It also notes the safe bulk-delete implementation, but does not explicitly mention alternatives like 'delete_memory' for single deletions or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses event types and ordering but lacks details on potential behavioral traits like result limits, performance implications, or whether it is read-only (though implied). The output schema likely covers return value structure but this is not mentioned in the description.
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 sentence that efficiently conveys purpose, included event types, and ordering, with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description is fairly complete. It explains the content and ordering of results. However, it could mention any time range restrictions or implicit limits, though these may be covered by the output schema.
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 single parameter memory_id is described in the schema with 'Exact memory UUID whose change history to fetch.' Since schema coverage is 100%, the description adds no additional meaning beyond what the schema already provides, earning a baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly explains the tool fetches a full change timeline of a memory, listing specific event types (ADD, UPDATE, SUPERSEDED, DELETE) and ordering (oldest first). It distinguishes from sibling tools like get_memory (current state) and update_memory (modify).
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 for viewing history but does not explicitly state when to use versus alternatives. No exclusions or when-not-to-use guidance is provided, relying on implied context from sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses the two execution paths and the exact response contracts for each. It covers both success and error cases. While it lacks details on authentication or rate limits, it provides essential behavioral context for an AI agent.
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 extremely concise, front-loaded with the action, and uses a clear bullet-like structure for the response contract. Every sentence provides necessary information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, 1 required) and the presence of an output schema described inline, the description covers the main behavior, response contracts, and a key prerequisite. It does not elaborate on edge cases like conflicting text and messages, but the schema addresses that. Overall, it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explicitly stating the constraint that at least one of user_id, agent_id, or run_id is required, which is not present in individual parameter descriptions. This enhances parameter semantics.
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 'Store a new memory', specifying the action and resource. It adds a prerequisite about required identifiers. While it distinguishes from siblings like 'delete_memory' or 'get_memories', it does not explicitly contrast with 'add_document', but the purpose is clear enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the async vs sync path based on the 'infer' parameter and how to poll for async results. It gives a prerequisite (one of user_id, agent_id, run_id). However, it does not provide exclusions for when not to use this tool compared to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It clearly describes the output (depth, counts, etc.) and implies a read-only operation. Could explicitly mention it is non-destructive, but the context makes this clear.
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?
Single sentence with front-loaded purpose and bullet-like list of metrics. Every phrase adds value, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and existence of an output schema, the description fully covers what an agent needs: the tool returns queue health metrics. No additional details needed for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, and schema coverage is 100%. The description adds context about the output beyond the schema, but parameter semantics dimension is satisfied by the absence of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the tool returns health metrics of the async ingest queue, listing specific fields (depth, counts, age, drain time, worker alive). This clearly distinguishes it from sibling tools like add_document or memory_task_status, which have different purposes.
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 for monitoring queue health but does not explicitly state when to use this tool versus alternatives (e.g., after ingestion or periodically). No guidance on exclusion criteria or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It transparently lists possible states (pending, processing, done, failed_retryable, dead) and explains result fields including 'result.memory_ids', 'result.events' with SUPERSEDED markings, and 'last_error'. It does not indicate destructive behavior, which is appropriate for a read-only status check.
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, well-structured paragraph with clear front-loading of purpose. Every sentence adds value: states enumeration, result fields, error explanation. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description provides rich behavioral context (states, result fields, error handling) that fully covers the tool's functionality. It includes details like SUPERSEDED events which add valuable context.
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 coverage is 100%, and the description of task_id ('Task id returned by a queued add_memory call (tsk_...).') essentially repeats the schema's description. The description adds no new semantic value beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the status of an asynchronous add_memory task, with specific verb 'status' and resource 'memory_task'. It distinguishes from siblings like add_memory and memory_queue_status by focusing on a single task's status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on how to interpret results (fetch memories with get_memory, check last_error for failure) and implies use after an add_memory call. However, it does not explicitly contrast with sibling memory_queue_status or give explicit when-not-to-use scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavior: asynchronous operation, immediate return with status, polling mechanism, deduplication logic, error conditions (queue unavailable), and technical details of text extraction (poppler, vision model).
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 (4-5 sentences) and front-loaded with the purpose. However, it includes some implementation details (poppler, vision model) that may not be essential for tool selection.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, async, polling, dedup), and absence of annotations and output schema (though return format is described), the description is complete. It covers inputs, process, response, polling, duplicate handling, and failure modes.
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, so the description adds minimal meaning beyond what the schema already provides. It mentions 'force=true' and 'file_path' but does not elaborate on other parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: ingest PDF or image, extract text per page, chunk, and extract facts. It specifies the types of inputs (PDF/image) and distinguishes from sibling tools like add_memory by focusing on document ingestion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on how to use the tool (asynchronous, poll results, handle duplicates) and mentions no synchronous fallback. However, it does not explicitly compare with sibling tools or specify when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description thoroughly covers the async behavior, re-embedding process, no double-apply guarantee, and polling mechanism, providing full transparency.
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 a single well-structured paragraph that front-loads the main action and then explains async details, though it could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of async behavior and an existing output schema, the description provides all necessary context for correct invocation and result handling, including polling instructions.
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 coverage is 100% and parameter descriptions are adequate (e.g., 'Replacement text for the memory.'). The description adds context about the update but does not significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool updates an existing memory's text, with the verb 'update' and the resource 'memory's text', distinguishing it from siblings like add_memory or delete_memory.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use this tool (to update existing memory) and provides context on async behavior and polling, but does not explicitly list when not to use it or alternatives.
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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