Memento
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: store creates/updates, search finds, recall retrieves full content, delete removes, and list_namespaces discovers domains. No overlapping functionality exists, and the descriptions explicitly differentiate between search and recall.
Naming Consistency5/5All tool names follow a consistent memory_verb pattern (store, search, recall, delete, list_namespaces). This makes the set predictable and easy to navigate.
Tool Count5/5With 5 tools, the server is well-scoped for a memory management system. Each tool addresses a distinct operation without unnecessary redundancy or bloat.
Completeness5/5The tool set covers the full lifecycle of memory management: create/update (memory_store), read (memory_recall), search (memory_search), delete (memory_delete), and discovery (memory_list_namespaces). There are no obvious gaps or dead ends.
Average 4.3/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No high-severity vulnerability alerts
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses persistence and searchability, which are important behavioral traits, but it does not explain update semantics (e.g., whether fields are merged or replaced) or any side effects. This is a noticeable gap for a write tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (four sentences, ~35 words) and front-loaded with the core action. Every sentence adds value: purpose, update behavior, persistence/searchability, and content best practices. No filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a store/upsert tool with six parameters and no output schema, the description covers the essential context: what it does, how to update, persistence, and searchability. It lacks details on return values or edge cases like TTL or namespace handling, but those are documented in the schema. Overall, it's sufficiently complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 six parameters. The description adds content-writing guidance ('specific, front-loads key information, one concept per entry') that complements the schema but does not substantially enhance understanding of parameter semantics beyond it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Uses a specific verb pair 'create or update' with resource 'a memory', and the tool's name clearly indicates the write operation. It contrasts with siblings (search, recall, delete, list) by being the only write tool, and the description reinforces this.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context that memories are persistent and searchable, implying this tool is for storing information. However, it does not explicitly mention alternatives like memory_search or memory_delete, nor does it state when not to use it. Still, the purpose is unambiguous and the content guidance is useful for effective use.
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 discloses that deletion is 'soft' and that the entry is 'excluded from future searches', which are key behavioral traits. However, it does not mention whether the deletion is reversible, what happens to the underlying data, or behavior on missing IDs, but the core behavior is well disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and each sentence adds value. There is no redundant information or unnecessary detail. It is exemplary in conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple tool with two required parameters and no output schema. The description explains the tool's purpose, effect, and required context. The sibling tools are available for context, and no additional behavioral details seem necessary for correct invocation. The description is complete for this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'id' and 'namespace' having clear descriptions. The tool description adds 'Requires the namespace', but this is already evident from the schema. No additional parameter semantics are provided, 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Soft-delete a memory by ID' and the effect 'excluded from future searches', which distinguishes it from sibling tools like memory_store, memory_search, memory_recall, and memory_list_namespaces. The verb and resource are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (to soft-delete a memory) and mentions a prerequisite (requires namespace), but it does not explicitly state when not to use it or compare against alternatives. The usage context is clear enough, but no exclusions or alternatives are named.
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?
The description discloses no annotation details since none are provided, so it carries the full burden. It implies read-only behavior via 'Fetch' and hints at potential cost with 'Only recall what you actually need,' but it does not explain what happens with invalid IDs, return structure, or any failure modes. This is minimal but adequate for a simple retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences each serve a distinct purpose: stating the action, giving usage context, and providing a best-practice caution. There is no redundancy or filler, and the most important information is front-loaded in the first sentence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter, no annotations, and no output schema, the description covers purpose, usage context, and a cost-conscious guideline. It does not explain the return format or error behavior, but the simplicity of the tool and the clear linkage to memory_search make this sufficiently complete for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the parameters with a description for 'ids.' The tool description adds contextual usage ('Use after memory_search') but does not deepen parameter semantics beyond the schema—it does not clarify array size limits, duplicate handling, or ID format specifics. This aligns with the baseline for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Fetch full content for specific memory IDs,' which clearly states the tool's action (fetch) and target (memory IDs). It also distinguishes itself from siblings by explicitly referencing memory_search as a prior step, making it clear that this tool retrieves details for already-found IDs rather than searching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Use after memory_search to retrieve complete entries for the most relevant results,' providing a direct when-to-use statement. The instruction 'Only recall what you actually need' adds a concrete exclusionary guideline about avoiding unnecessary fetches. This is clear and actionable.
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 of behavioral disclosure. The verb 'List' clearly implies a read-only operation, and the phrase 'with entry counts' adds insight into the output scope. No side effects or limitations are mentioned, but for a listing tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences. The first sentence front-loads the action and result, and the second sentence adds practical usage context. There is no wasted wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no parameters and no output schema, the description provides sufficient context: it explains what is returned (namespaces with entry counts) and when it should be invoked (before searching). This is complete for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline for this dimension is 4. The description correctly avoids describing parameters since none exist, and it does not need to compensate for any schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('List') and resource ('all available namespaces') with the added detail of 'entry counts', making it clear what the tool does. It distinguishes itself from sibling tools (memory_store, memory_search, etc.) by focusing on namespace discovery rather than data manipulation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage context: 'Use this to discover what domains of knowledge exist before searching.' This implies the tool is a preliminary discovery step before using search, though it does not explicitly name the alternative sibling or state 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 provided, the description carries the full burden. It discloses that only snippets (~150 chars) are returned, not full content, and mentions the BM25 ranking algorithm. This is valuable behavioral context that helps the agent set expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the primary purpose, and every sentence adds value. It is concise and well-structured with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and 100% schema coverage, the description covers the key return behavior (snippets, not full content) and provides a pointer to the complementary tool. There is no output schema, so this disclosure is sufficient for an agent to understand what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already explains every parameter (query, limit, namespace, tags). The description briefly mentions namespace and tags for scoping, but adds no new meaning beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Search memories using BM25 ranking,' which clearly identifies the verb (Search) and resource (memories). It explicitly differentiates from the sibling tool memory_recall by noting this returns snippets, not full content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly instructs to use memory_recall for full content, providing a clear alternative. It also advises scoping with namespace and tags for better relevance, giving practical guidance on when to use this tool effectively.
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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