Multi-Memory MCP Server

by DanNsk

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a specific resource or action: entities, relations, observations, categories, graph reading, and search. The deletion tools are clearly differentiated by object type (entities, observations, relations, categories). Retrieval tools (open_nodes, read_graph, search_nodes) serve distinct purposes.
Naming Consistency4/5
All tool names follow a verb_noun pattern with lowercase and underscores (e.g., create_entities, delete_observations). However, the verbs vary: 'add' vs 'create' for creation, and 'open' is an unusual choice for retrieval, introducing slight inconsistency.
Tool Count5/5
With 11 tools, the server covers the essential operations for managing a knowledge graph (CRUD for entities, relations, observations, plus categories, graph reading, and search). The count is well within the typical 3-15 range and feels appropriate for the domain.
Completeness3/5
The tools cover create, read, delete, and search operations, but lack update functionality for entities and relations (e.g., update_entity, update_relation). Also, categories can only be listed and deleted, not created or renamed. These gaps limit completeness.
Average 3.7/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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?
The description discloses that it creates relations, returns IDs, and allows updates via override. However, it omits details on error handling (e.g., missing endpoints), side effects, or permissions. With no annotations, the description carries full burden but provides only partial coverage.
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?
Three sentences, front-loading the main purpose. Concise and efficient, though could be slightly more structured (e.g., bullet points for clarity).
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 output schema, the description mentions return value (IDs) and override behavior. However, it lacks context on error scenarios, default category, or contrast with sibling tools like 'delete_relations'. Adequate but not thorough.
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 67%, so baseline is 3. The description adds value by explaining endpoint specification (id or name/type) and override behavior, but much of this repeats schema info. It does not compensate for the missing description on the 'relations' parameter.
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 creates multiple relations between entities and specifies how endpoints are identified. However, it does not explicitly differentiate from siblings like 'create_entities' or 'delete_relations', leaving some ambiguity.
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 an override option but does not discuss exclusions or prerequisites, such as needing entities to exist first.
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 provided, the description carries full burden but only states that it deletes observations. It does not disclose whether deletion is irreversible, requires permissions, or has side effects (e.g., cascade deletions). The deletion behavior is implied but not elaborated.
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 (two sentences, 16 words), front-loads the purpose, and has no wasted content. Every word is necessary and informative.
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 no output schema and no annotations, the description should cover behavior like return values, error handling, and side effects. It does not address what happens if observations are not found, whether multiple deletions are atomic, or if any prerequisites exist. The description is incomplete for a deletion tool.
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 50%, but the description adds value by concisely summarizing the two identification patterns: 'by observation id OR by entity identifier + observationType + source.' This clarifies the relationship between parameters beyond what individual field descriptions provide. However, the schema already has comparable descriptions for each parameter, so the added value is moderate.
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 deletes observations and specifies two identification methods (by observation ID or by entity identifier + observationType + source). This differentiates it from sibling tools like delete_entities and delete_relations, which target different resources.
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?
The description provides no explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or conditions for use. The agent must infer usage based on the resource name ('observations' vs siblings).
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 the full burden of behavioral disclosure. It states that it returns entities with IDs, but does not mention if the operation is read-only, requires authentication, or what happens if entities are not found. This is insufficient for a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences, no wasted words, and the key purpose is front-loaded. Every sentence adds value.
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?
The tool has no output schema and no annotations. The description does not explain the return format in detail, error behavior, or prerequisites. For a simple retrieval tool, it lacks completeness in contextualizing the full behavior.
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 baseline is 3. The description adds a brief clarification on the OR condition between id and name/entityType, but mostly reiterates schema descriptions. It does not provide additional semantics beyond what is already in 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 verb 'Open' and the resource 'specific entities', and explains how to specify them (by id or name/entityType). This distinguishes it from siblings like search_nodes (search) and create_entities (create).
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 you know entity identifiers, but it does not explicitly state when not to use it or provide alternatives. The sibling search_nodes is a natural alternative for unknown entities, but no direct comparison is made.
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 provided, the description carries the full burden. It discloses that relations are also deleted (cascading behavior), but does not state whether the operation is permanent, require authorization, or handle errors. The basic destructive effect is clear, but additional details (e.g., irreversibility) would improve transparency.
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 two sentences long, front-loading the main action: 'Delete entities and their relations.' Every sentence adds value, with no unnecessary words or repetition.
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 the tool's simplicity (2 parameters, 1 required, no output schema) and 100% schema coverage, the description covers the core behavior and identification method. However, it lacks details on return values, error handling, behavior when both id and name/entityType are provided, and whether the action is reversible. This is adequate but not fully 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 coverage is 100%, so the schema already documents all parameters. The description reinforces the two identification methods (id vs name/entityType) but does not add new constraints or examples. It provides mild additional clarity but not significant extra meaning.
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 action ('Delete entities and their relations') and specifies the identification method (by id or name/entityType). This provides a specific verb and resource, distinguishing it from sibling tools like create_entities or delete_relations.
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?
The description offers no guidance on when to use this tool versus alternatives such as delete_relations (for relations only) or delete_category. It does not mention prerequisites, context, or exclusions, leaving the agent to infer usage from the name alone.
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?
Without annotations, the description adequately indicates the destructive nature by stating 'delete' and 'all its contents,' but lacks details on reversibility, permissions, or side effects.
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, well-structured sentence that efficiently conveys the tool's purpose without unnecessary 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 tool with one parameter and no output schema, the description covers the essential behavior. It could mention what happens to related data or if the action is reversible, but it is largely sufficient given the sibling 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?
The single parameter 'category' has a description in the schema that matches the purpose. The description adds no additional meaning beyond the schema's documentation.
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 action ('Delete'), the resource ('entire memory category'), and the scope ('all its contents'), effectively distinguishing it from sibling tools that delete specific items.
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 vs. alternatives like delete_entities or delete_observations. It does not mention when not to use it or what prerequisites are needed.
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 must disclose all behavioral traits. It states return contents but omits safety aspects (e.g., read-only nature), performance implications (potentially large result), or side effects. The term 'Read' hints at non-modifying behavior but is not explicit.
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 two sentences, front-loaded with the action, and contains no unnecessary words. Every word provides information.
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?
For a simple read tool with no output schema, the description covers the basics but lacks detail on return format beyond presence of IDs. It does not mention limits, pagination, or structure of entities/relations. Competes well with sibling complexity but incomplete without 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 only parameter 'category' is fully described in the schema (default, purpose). The description adds no extra meaning beyond what the schema provides. With 100% schema description coverage, 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 reads the entire knowledge graph and specifies what is returned (all entities and relations with IDs). This distinguishes it from siblings like search_nodes or list_categories which have narrower scope.
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 a full graph read but lacks explicit guidance on when not to use it or alternatives. Sibling tools are provided externally but not referenced in the description.
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 is the sole source for behavioral traits. It states the tool lists all categories, implying a read-only operation, but does not disclose any additional behaviors like whether results are paginated or if there are side effects.
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—a single, clear sentence. Every word is meaningful and front-loaded with the action and object.
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, parameterless list tool, the description is nearly complete. It could mention if the list is ordered or filtered, but given no output schema and low complexity, it adequately informs the agent.
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?
There are no parameters, so the description does not need to add meaning beyond the schema. The schema coverage is 100% (no parameters), meeting the baseline for this dimension.
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 'List all available memory categories' uses a specific verb and resource, clearly stating the tool's function. It distinguishes from sibling tools that perform different actions like adding observations or creating entities.
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 (e.g., search_nodes or read_graph). There is no context for when listing categories is appropriate or when other tools might be better.
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 provided, so description carries burden. Mentions uniqueness constraint and override behavior, but misses details on idempotency, permissions, or error handling for non-existent entities.
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 focused sentences plus a constraint sentence. No fluff, front-loaded with main verb.
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?
Covers purpose, identification, constraint, override, return value. Missing details on entity existence validation and error scenarios, but adequate for a well-structured 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?
Adds context beyond schema: entity identification alternatives, return value, and constraint. Schema covers most parameters but description enriches 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?
Description clearly states 'Add new observations to existing entities' and specifies entity identification methods and return value. Distinguishes from siblings like delete_observations or create_entities.
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?
Implies usage for adding observations but lacks explicit guidance on when not to use or alternatives. No comparison with sibling tools.
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 full burden for behavioral disclosure. It explains the input methods but omits side effects, reversibility, permissions, or rate limits—important for a deletion operation.
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, information-dense sentence that front-loads the purpose. It could be slightly restructured for readability, but contains no superfluous content.
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?
No output schema exists, yet the description does not indicate what happens after deletion (e.g., success message, deleted count). It also lacks guidance on choosing among sibling tools, though the tool's specific purpose is clear.
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?
The schema has 100% coverage with individual property descriptions. The description adds value by grouping parameters into the three logical alternatives (by id, by entity IDs, by entity names), clarifying the trade-offs 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 relations' and specifies three explicit methods (by relation id, by entity IDs, by entity names), making the tool's purpose obvious and distinguishing it from sibling tools like delete_entities or delete_observations.
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 guidance on how to specify which relations to delete (by id, entity IDs, or entity names), but does not explain when to use this tool versus alternatives like delete_entities or 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description covers return values (assigned IDs), uniqueness constraints, and override behavior. However, it lacks details on error handling (e.g., behavior on duplicate without override), idempotency, or authentication needs.
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 plus a line for constraints. Front-loaded with purpose. Every sentence adds value, no redundant information.
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 the complex nested structure (entities with observations) and no output schema, the description covers key points but omits specifics like error messages, partial failure behavior, or the exact effect of override (replace vs update). Adequate but not exhaustive.
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?
With 67% schema description coverage, the schema already documents most parameters. The description adds value by explaining uniqueness constraints and the override flag, which goes beyond the schema's individual parameter descriptions.
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 creates multiple new entities in the knowledge graph and returns assigned IDs. It distinguishes itself from siblings like add_observations (which adds to existing entities) and create_relations.
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 constraints on uniqueness and when to use override, giving context on usage. However, it does not explicitly exclude cases when alternatives should be used (e.g., when to use add_observations instead of including observations).
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?
As annotations are absent, the description carries full burden. It explains the BM25 algorithm, relevance sorting, and detailed FTS5 query syntax with auto-conversion. Missing are potential error conditions or permission requirements, but core behavior is well-covered.
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 with two sentences that front-load the purpose and then detail query syntax. Every sentence adds value without redundancy.
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 lacks details about the structure of returned entities (e.g., fields, scores) and pagination behavior, leaving gaps for an agent to understand the output. While the query behavior is well-explained, the absence of output schema means more completeness is needed.
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?
The schema provides 100% coverage, but the description adds valuable context for the query parameter by explaining FTS5 syntax and auto-conversion, enriching semantic meaning beyond the schema descriptions.
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 identifies the tool as a full-text search over entities with BM25 ranking and relevance sorting. This distinguishes it from sibling tools like read_graph or add_observations, which are not search-focused.
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?
No explicit guidance on when to use this tool versus alternatives is provided. Since no other search tool exists among siblings, the usage is implied, but explicit recommendations for scenarios or exclusions would improve the score.
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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