ChatCrystal

Server Quality Checklist

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Latest release: v0.5.7
Disambiguation5/5
Each tool serves a clearly distinct purpose: getting full notes, listing summaries, semantic search, task-specific recall, relation retrieval, validation, and writing. No overlapping functionality.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using lowercase and underscores, e.g., get_note, list_notes, write_task_memory, ensuring predictability.
Tool Count5/5
With 7 tools, the set is well-scoped for a knowledge base server, covering creation, retrieval, search, and validation without being overwhelming or sparse.
Completeness3/5
The tool surface covers core operations but lacks update and delete capabilities for notes, which may create dead ends if an agent needs to modify or remove a memory.
Average 3.9/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 2 of 2 community issues answered or closed in the last 6 months
- 60 commits in the last 12 weeks
- Last stable release on June 27, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
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.
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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 indicates a read operation and lists included fields but lacks details on return format, permissions, or constraints. With no annotations provided, the description carries the burden for transparency, and while adequate for a simple read, it could be more explicit.
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 with no redundancy, but it could be slightly more structured (e.g., bullet points for output fields) without increasing verbosity. Still, it is concise and clear.
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 tool's simplicity (one parameter, no output schema, no annotations), the description adequately covers purpose and output. However, it does not mention return format or prerequisites, which would be beneficial for complete 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 description coverage is 100% (the only parameter 'id' has a description 'Note ID'). The tool description does not add additional meaning beyond the schema; therefore, baseline score of 3 applies.
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 ('Get') and the resource ('full content of a note'). It lists specific included elements (title, summary, key conclusions, code snippets, tags), making the tool's function distinct from siblings like list_notes or get_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?
No guidance is provided on when to use this tool versus alternatives (e.g., list_notes for metadata or search_knowledge for searching). The agent must infer usage solely from the description and sibling names.
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 must carry behavioral disclosure. It only states what is returned but does not mention safety (e.g., read-only), authentication needs, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundant words. It is appropriately sized for the task.
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?
With one parameter and no output schema, the description is minimal. It states the output includes relationship type and confidence score but does not specify if results are paginated, ordered, or empty-possible. Adequate for a simple tool but lacks completeness.
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 noteId. The schema already describes it as 'Note ID to find relations for'. The description adds no additional meaning beyond that.
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 'Get', the resource 'related notes', and specifies the output includes 'relationship type and confidence score'. It distinguishes from sibling tools like get_note and list_notes by focusing on relationships.
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 related notes for a given note, but does not provide explicit when-not or alternative tools. No guidance on filtering 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?
The description mentions it returns notes ranked by relevance, indicating a read and search behavior, but lacks details on pagination, result format, no-result behavior, or any side effects. With no annotations, more disclosure would be beneficial.
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 concise with two sentences, front-loading the core purpose. There is no unnecessary text, making it efficient for an AI agent to parse.
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 tool with two parameters and no output schema, the description covers the main functionality but omits details on the return format of notes and edge cases. It is adequate but not fully comprehensive.
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 already provides descriptions for both parameters (query and limit). The tool description adds no additional meaning beyond what the schema states, thus 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 performs semantic search across a knowledge base and returns ranked notes. It distinguishes itself from siblings like list_notes (general listing) and get_note (retrieving a specific note) by specifying the search nature and ranking.
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 such as list_notes or recall_for_task. The description only states what it does without contextual recommendations.
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?
Discloses quality validation and skip behavior for weak entries, but with no annotations, it misses details like side effects, auth requirements, rate limits, or error handling. The description carries the full burden due to missing annotations.
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?
Description is a single paragraph that is front-loaded with purpose and criteria. It includes examples and exclusions without excessive verbosity. Could be slightly more concise but effectively conveys key information.
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 complex nested parameters and no output schema, the description covers purpose, usage conditions, and quality expectations. It lacks explanation of return values (receipts) but otherwise is fairly 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 parameters are well-documented in the schema. The description adds context on quality criteria but does not enhance parameter 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool persists high-quality task memories as ChatCrystal notes with specific criteria (title, summary, conclusions, reusable lesson). It distinguishes from weak auto writebacks but does not explicitly differentiate from sibling tools like validate_task_memory or recall_for_task.
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?
Provides explicit when-to-use (only for high-quality, durable lessons) and when-not-to-use (one-time checks, status reports, vague claims). Mentions that weak writebacks are skipped. Lacks explicit alternatives or comparison to sibling tools.
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: 'Dry-run validation', 'has no side effects', 'never writes to the knowledge base', and describes return values (acceptance, rejection reason, warnings, materialized note fields). No contradictions.
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?
Three sentences efficiently cover purpose, usage, and behavior without fluff. Front-loaded with primary action, then usage guidance, then behavior and returns. Every sentence adds value.
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 moderate complexity (5 params, nested objects) and no output schema, the description covers return fields (acceptance, rejection reason, warnings, materialized note fields) and states the tool is for validation. Could elaborate more on what constitutes 'high-quality' criteria but is sufficient for an agent to use correctly.
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 baseline is 3. The description adds context about what the tool does overall but does not discuss individual parameters beyond what the schema already provides. It does not compensate for any missing schema details.
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 validates a candidate task memory before persisting, using specific verbs ('validate') and resources ('task memory'). It distinguishes itself from sibling write_task_memory with the 'Dry-run' qualifier and explicitly names it as the counterpart.
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?
Provides clear context: 'Use this after meaningful work and before persisting a lesson'. States it has no side effects, indicating safe dry-run usage. However, does not explicitly state when not to use or list alternatives beyond implying write_task_memory is the next step.
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 discloses output is metadata/summaries not full content, and implies read-only nature. Missing info on auth or rate limits but adequate for this simple 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?
Three sentences, front-loaded with purpose, no wasted words. Efficient and structured.
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 simple tool with 3 params, no output schema, description fully covers what the tool does, when to use, parameter roles, and output 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%, so baseline is 3. Description adds context about pagination and search being literal, but much is already in schema descriptions. No significant extra meaning 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 it lists note summaries for browsing, and explicitly distinguishes from sibling tools search_knowledge and get_note. Specific verb-resource pair.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when to use (browsing, filtering by tag or keyword) and when not (semantic search or full note retrieval), naming alternatives.
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?
No annotations provided, so description carries full burden. It states the tool is read-only, returns ranked memories plus optional related-note context, and writes nothing. This sufficiently discloses behavioral traits without contradictions.
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 paragraph that is front-loaded with purpose and well-structured. Every sentence adds value; no wasted words. Efficiently covers usage, mode, and exclusions.
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 complexity (3 parameters, nested object, no output schema), description explains return values (ranked memories plus optional context) and main use cases. Lacks details on exact output format but sufficient for agent understanding.
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 baseline is 3. The description adds some context (e.g., use debug mode for errors) but mainly restates schema information. No significant additional semantics 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?
The description clearly states the tool retrieves reusable task memories before starting substantive coding work, with specific verb ('Retrieve') and resource ('reusable task memories'). It distinguishes from sibling tool search_knowledge by specifying when to use that alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use (at beginning of implementation, debugging, etc.) and when not to (ad hoc note search via search_knowledge). Also gives mode-specific instructions (debug mode for errors) and lists optional parameters for context.
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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