lafe-blog MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation2/5
There is significant ambiguity between 'create_note' and 'write_note', which appear to serve the same purpose of creating/writing notes, making it unclear which tool to use for note creation. The blog-related tools ('post_blog' and 'validate_blog') are distinct from each other but overlap conceptually with the note tools in the broader content creation domain.
Naming Consistency4/5The tool names follow a consistent verb_noun pattern (e.g., create_note, post_blog, validate_blog, write_note), which is predictable and readable. The only minor deviation is that 'write_note' uses 'write' instead of 'create', but it still fits the overall naming convention.
Tool Count3/5With 4 tools, the count is borderline thin for a blog server, as it might lack operations like updating, deleting, or listing notes and blogs. However, it covers basic creation and validation, so it's not severely mismatched but feels slightly under-scoped.
Completeness2/5There are significant gaps in the tool surface for a blog server: it includes creation and validation for blogs and notes but lacks update, delete, list, or get operations for either resource. This incomplete coverage will likely cause agent failures when trying to manage content beyond initial creation.
Average 2.9/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. 'Write a new note' implies a creation/mutation operation but doesn't specify permissions needed, whether the note is saved permanently, what happens on failure, or any rate limits. For a mutation tool with zero annotation coverage, this is inadequate.
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 extremely concise - just three words that directly state the tool's function. There's zero wasted language, and the meaning is immediately clear despite its brevity. This is an example of efficient communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what happens after writing the note (where it's stored, what format it returns, error conditions). Given the complexity of a write operation and lack of structured metadata, more context is needed.
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 description adds no parameter information beyond what's already in the schema (which has 100% coverage). Both parameters (title and content) are fully documented in the schema with clear descriptions. The baseline score of 3 is appropriate when the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Write a new note' clearly states the action (write) and resource (note), but it's quite basic and doesn't distinguish from the sibling tool 'create_note' which appears to serve a similar purpose. The description is functional but lacks specificity about what makes this tool different from its sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the sibling 'create_note' or other related tools like 'post_blog' and 'validate_blog'. There's no mention of prerequisites, alternatives, or appropriate contexts for selecting this specific tool.
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 for behavioral disclosure. 'Create a new note' implies a write/mutation operation but doesn't specify permissions needed, whether creation is idempotent, error conditions, or what happens on success. For a mutation tool with zero annotation coverage, this is inadequate.
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 a single, efficient sentence with zero wasted words. It's appropriately sized for a simple creation tool and immediately communicates the core purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, error handling, or behavioral constraints. Given the complexity of a creation operation, more context about outcomes and limitations would be needed for the agent to use it effectively.
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 parameters ('title' and 'content') fully documented in the schema. The description adds no additional parameter information beyond what the schema already provides, so it meets the baseline for high schema coverage without compensating value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create a new note' clearly states the action (create) and resource (note), making the tool's purpose immediately understandable. It distinguishes from 'post_blog' and 'validate_blog' by focusing on notes rather than blogs, though it doesn't explicitly differentiate from 'write_note' which might be a similar operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'write_note' or 'post_blog'. There's no mention of prerequisites, appropriate contexts, or exclusions, leaving the agent to infer usage based on tool names alone.
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 the full burden of behavioral disclosure. It mentions 'Zod validation' but doesn't explain what this entails (e.g., validation errors, requirements) or other traits like authentication needs, rate limits, or mutation effects. This is inadequate for a write operation 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 a single, efficient sentence with zero waste. It's front-loaded with the core action and includes a relevant detail ('Zod validation'), making it appropriately sized and structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a 9-parameter mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, usage context, and output expectations, leaving significant gaps for an agent to understand the tool fully.
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 description coverage is 100%, so the input schema fully documents all 9 parameters. The description adds no additional meaning beyond the schema, such as explaining 'Zod validation' in relation to parameters. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Post') and resource ('blog article to the CMS API'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'create_note' or 'write_note', which might have overlapping functionality, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'create_note' or 'validate_blog'. It mentions 'Zod validation' but doesn't explain if this is a prerequisite or how it relates to usage, leaving the agent without clear context for selection.
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. It discloses that validation occurs 'without posting', indicating a read-only, non-destructive operation. However, it lacks details on behavioral traits like error handling, output format, rate limits, or permissions needed. For a validation tool with zero annotation coverage, this is insufficient.
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 a single, efficient sentence: 'Validate blog data using Zod schema without posting'. It is front-loaded with the core purpose, has zero wasted words, and appropriately sized for the tool's complexity, earning a top score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 parameters, 4 required), no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It covers the basic purpose but lacks details on validation rules, error responses, or how results are returned, making it inadequate for effective tool use without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate by explaining parameters. It mentions 'blog data' but does not detail what fields are validated (e.g., title, content) or their semantics. With 9 parameters and no schema descriptions, the description adds minimal value beyond the schema's structure, failing to adequately clarify parameter meanings.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Validate blog data using Zod schema without posting'. It specifies the verb (validate), resource (blog data), and method (Zod schema), and distinguishes it from siblings by emphasizing 'without posting'. However, it doesn't explicitly differentiate from validation-like siblings if any exist, keeping it at 4 rather than 5.
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 usage context by stating 'without posting', suggesting this tool is for validation before creation/posting, which aligns with siblings like 'post_blog'. However, it lacks explicit guidance on when to use this vs. alternatives (e.g., 'create_note' or 'write_note'), no exclusions, and no prerequisites, making it adequate but with gaps.
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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