SafeMarkdownEditor MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting different document operations, but there is some overlap between get_document and load_document where both retrieve document content. The descriptions clarify that load_document includes analysis while get_document focuses on content/structure, but an agent might initially confuse them.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern with snake_case naming (e.g., analyze_document, delete_section, get_document). The verbs are clear and appropriate for the actions, making the tool set predictable and readable.
Tool Count5/5
With 10 tools, this is well-scoped for a Markdown editor server, covering core operations like loading, analyzing, reading, writing, and manipulating sections. Each tool has a clear role without unnecessary duplication, fitting typical server sizes.
Completeness5/5
The tool set provides comprehensive coverage for document management, including CRUD operations for sections (list, get, insert, update, delete, move) and full document handling (load, get, analyze, save). There are no obvious gaps for the domain of editing and analyzing Markdown files.
Average 3/5 across 10 of 10 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 is failing
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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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 the full burden of behavioral disclosure. It mentions that the document will be saved if auto_save is True, which adds some context, but fails to disclose critical behavioral traits such as whether the deletion is permanent, what happens to nested sections, error conditions, or the impact of the backup and validation_level parameters. This leaves significant gaps for a destructive 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 appropriately sized with two sentences that are front-loaded with the core action. There is no wasted text, but it could be slightly more structured by explicitly listing key parameters or behaviors in a bullet-point format for clarity.
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 the complexity of a destructive operation with 6 parameters, 0% schema description coverage, no annotations, and an output schema (which reduces the need to describe return values), the description is incomplete. It lacks details on parameter semantics, behavioral risks, and usage context, making it insufficient for safe and effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does 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 only mentions 'ID or heading' and 'auto_save', covering 2 out of 6 parameters (document_path, section_id, heading, auto_save, backup, validation_level). This partial coverage is inadequate, as key parameters like backup and validation_level are left unexplained, failing to add sufficient meaning beyond the schema.
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 verb 'Delete' and the resource 'a section by ID or heading', making the purpose unambiguous. However, it doesn't explicitly distinguish this tool from sibling tools like 'move_section' or 'update_section' in terms of destructive nature, which would require a 5.
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 guidance on when to use this tool versus alternatives like 'move_section' or 'update_section', nor does it mention prerequisites such as needing the document to be loaded first. It only mentions the auto_save condition, which is insufficient for comprehensive usage guidance.
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 the auto-save behavior, which is useful, but fails to cover critical aspects like required permissions, error handling, what happens if the position is invalid, or whether the operation is reversible. For a mutation tool with 7 parameters, this leaves significant gaps in understanding its behavior.
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 brief and front-loaded with the main action, consisting of two sentences. However, the second sentence about auto-save could be more integrated, and overall it lacks the depth needed for a tool with 7 parameters, making it somewhat under-specified rather than optimally concise.
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 the complexity (7 parameters, no annotations, but with an output schema), the description is incomplete. It doesn't address key contextual elements like what a 'section' entails, how 'position' is determined, or the implications of 'validation_level'. The presence of an output schema mitigates the need to describe return values, but other gaps remain significant.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does 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 only references 'auto_save' indirectly, without detailing what it does or how it interacts with other parameters like 'backup' or 'validation_level'. The core parameters (document_path, heading, content, position) are not explained at all, leaving their purpose and format unclear.
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 action ('Insert a new section') and the target ('at a specified location'), which distinguishes it from sibling tools like 'delete_section' or 'update_section'. However, it doesn't specify what kind of document or system it operates on, leaving some ambiguity about the resource context.
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 mentions that the document is saved if 'auto_save is True', which provides some operational context, but it doesn't explain when to use this tool versus alternatives like 'update_section' or 'move_section'. No explicit guidance on prerequisites or exclusions is provided.
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 that the document is saved if successful and auto_save is True, which hints at mutation and persistence behavior. However, it fails to address critical aspects like permissions needed, whether the operation is reversible, error handling, or what 'successful' entails, leaving significant gaps for a tool with 6 parameters.
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 brief and front-loaded with the core action in the first sentence, followed by a conditional detail. It avoids unnecessary verbosity, but the second sentence could be integrated more smoothly for better flow.
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 the tool's complexity (6 parameters, mutation operation) and the presence of an output schema, the description is incomplete. It lacks details on parameter semantics, behavioral traits like error handling or side effects, and does not leverage the output schema to explain return values. For a tool with no annotations and low schema coverage, this is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It only references 'auto_save' implicitly, without explaining other parameters like 'document_path', 'section_id', 'target_position', 'backup', or 'validation_level'. This adds minimal value beyond the schema, failing to clarify parameter meanings or usage.
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 action ('Move a section') and the resource ('section'), specifying the operation's goal ('to a different position'). It distinguishes from siblings like 'delete_section' or 'update_section' by focusing on repositioning, but does not explicitly contrast with 'insert_section' or 'list_sections' in terms of scope or function.
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 guidance on when to use this tool versus alternatives like 'update_section' for content changes or 'insert_section' for adding new sections. It mentions auto-save behavior but lacks context on prerequisites, error conditions, or typical use cases relative to sibling 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 provided, the description carries the full burden of behavioral disclosure. It mentions that 'The document will be saved after the operation if successful and auto_save is True', which adds some context about saving behavior. However, it fails to disclose critical traits like whether this is a destructive mutation, what permissions are required, error handling, or rate limits, leaving significant gaps for a tool that modifies content.
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 appropriately sized with two sentences that are front-loaded: the first states the core purpose, and the second adds behavioral context. There is no wasted text, and it avoids unnecessary elaboration, making it efficient and well-structured for quick comprehension.
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 the complexity of a mutation tool with 6 parameters, 0% schema coverage, no annotations, and sibling tools, the description is incomplete. It lacks details on parameter usage, error conditions, permissions, and how it differs from alternatives. While an output schema exists (which might cover return values), the description does not provide enough context for safe and effective tool invocation in this environment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does 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 only mentions 'auto_save' implicitly in the context of saving behavior, but does not describe the purpose or usage of other parameters like 'document_path', 'section_id', 'content', 'backup', or 'validation_level'. This leaves most parameters undocumented, failing to add meaningful semantics beyond the bare schema.
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 verb 'update' and the resource 'content of an existing section', making the purpose specific and understandable. It distinguishes from siblings like 'insert_section' (create new) and 'delete_section' (remove), though it doesn't explicitly name these alternatives. The purpose is not vague or tautological.
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 guidance on when to use this tool versus alternatives like 'insert_section' or 'move_section', nor does it mention prerequisites such as needing an existing document or section. It only implies usage through the phrase 'existing section', but lacks explicit context or exclusions for tool 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'analyze document structure and provide insights' but doesn't specify what kind of insights, whether this is a read-only operation, if it modifies the document, what permissions are required, or any rate limits. For an analysis tool with zero annotation coverage, this leaves significant behavioral gaps.
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 appropriately sized with a clear purpose statement followed by parameter documentation. The two-sentence structure is efficient with zero wasted words. The parameter documentation uses a clean Args: format that's easy to parse. It could be slightly more front-loaded by moving the parameter details to a separate section.
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 that an output schema exists, the description doesn't need to explain return values. However, for a 2-parameter analysis tool with no annotations, the description should provide more context about what 'analyze' means in practice, what kind of insights are provided, and how this differs from simply retrieving the document. The parameter documentation helps, but the overall context remains somewhat incomplete.
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 description explicitly documents both parameters with their purposes: 'document_path: Path to the Markdown file' and 'validation_level: Validation strictness - "STRICT", "NORMAL", or "PERMISSIVE"'. This adds substantial value beyond the input schema which has 0% description coverage. However, it doesn't explain the practical implications of different validation levels or provide examples of valid document paths.
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's purpose as 'Analyze document structure and provide insights' with a specific verb ('analyze') and resource ('document'). It distinguishes itself from siblings like 'get_document' (retrieval) or 'update_section' (modification) by focusing on analysis rather than basic CRUD operations. However, it doesn't explicitly differentiate from potential analysis-related siblings if they existed.
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 guidance on when to use this tool versus alternatives. With siblings like 'get_document' (retrieval), 'load_document' (loading), and 'list_sections' (listing), there's no indication whether this tool should be used instead of or in conjunction with them. The description lacks any 'when-to-use' or 'when-not-to-use' context.
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 'validation_level' but doesn't explain what validation entails (e.g., checking document format, handling errors) or the tool's behavior (e.g., returns a list, potential errors). This leaves significant gaps in understanding how the tool operates.
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 appropriately sized with a clear purpose statement followed by parameter explanations in a structured 'Args' section. It avoids unnecessary fluff, though the formatting with extra whitespace slightly reduces efficiency.
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 moderate complexity (2 parameters, no annotations) and the presence of an output schema (which handles return values), the description is minimally adequate. It covers the basics but lacks details on behavioral traits, usage context, and full parameter semantics, making it incomplete for optimal 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 0%, so the description must compensate. It adds meaning by explaining 'document_path' as 'Path to the Markdown file' and 'validation_level' with its possible values, which clarifies beyond the bare schema. However, it doesn't detail the format of 'document_path' (e.g., relative/absolute) or the effects of different validation levels, leaving some ambiguity.
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 verb 'List' and resource 'all sections in the document', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_section' or 'analyze_document', which would require a more detailed comparison.
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 guidance on when to use this tool versus alternatives like 'get_section' (for a single section) or 'analyze_document' (for broader analysis). It lacks context about prerequisites, such as whether the document must be loaded first, or exclusions for 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.
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 only states the basic action ('Get a specific section by ID') without mentioning any behavioral traits such as error handling, permissions required, rate limits, or what happens if the section doesn't exist. For a tool with no annotations, this is a significant gap in 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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a structured 'Args' section. There's no wasted text, and the information is organized efficiently. A 5 would require even more conciseness or bullet-point formatting, but this is very good.
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 that there's an output schema (which handles return values), the description doesn't need to explain outputs. However, with 3 parameters, no annotations, and multiple sibling tools, the description is incomplete: it lacks usage guidelines and behavioral context. It's minimally adequate but has clear gaps, especially for a tool in a complex environment with many alternatives.
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 description adds meaningful semantics for all three parameters: it explains that 'document_path' is a 'Path to the Markdown file,' 'section_id' is 'The section ID to retrieve,' and 'validation_level' specifies 'Validation strictness' with enum values. Since schema description coverage is 0% (no schema descriptions), this fully compensates by providing clear parameter meanings beyond just the schema's titles and types.
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's purpose: 'Get a specific section by ID.' This is a specific verb+resource combination (get + section). However, it doesn't explicitly distinguish this tool from its siblings like 'get_document' or 'list_sections,' which would require a 5.
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 guidance on when to use this tool versus alternatives. There are multiple sibling tools for document/section operations (e.g., get_document, list_sections, update_section), but the description doesn't mention any of them or specify contexts where get_section is preferred. This leaves the agent without usage direction.
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 'complete document content and structure' and validation levels, but lacks details on permissions, rate limits, error handling, or what 'complete' entails (e.g., metadata, formatting). This leaves significant gaps in understanding the tool's 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 appropriately sized and front-loaded, with the core purpose stated first in a clear sentence, followed by parameter details in a structured format. Every sentence earns its place without redundancy or fluff, making it highly efficient for quick comprehension.
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 moderate complexity (2 parameters, no annotations, but with an output schema), the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral context and usage guidelines. The presence of an output schema means return values needn't be explained, but overall completeness is limited.
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 description coverage is 0%, so the description must compensate. It adds meaning by explaining 'document_path' as 'Path to the Markdown file' and 'validation_level' with its allowed values and default, which clarifies beyond the bare schema. However, it doesn't detail path format or validation effects, preventing a perfect score.
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's purpose with the verb 'Get' and resource 'complete document content and structure', making it specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_section' or 'load_document', which limits its score to 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 Guidelines2/5
Does 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 such as 'get_section' for partial content or 'load_document' which might have different semantics. Without any context or exclusions, the agent must infer usage from the name alone, which is insufficient for optimal tool 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool loads and analyzes a document, implying read-only operations, but doesn't disclose critical behaviors such as error handling (e.g., what happens if the file doesn't exist), performance aspects (e.g., file size limits), or analysis specifics (e.g., what 'analyze' entails). This leaves significant gaps in understanding how the tool behaves beyond basic functionality.
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 appropriately sized and front-loaded, starting with the core purpose ('Load and analyze a Markdown document from a file path') followed by parameter details in a structured 'Args' section. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.
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 moderate complexity (2 parameters, no annotations, but with an output schema), the description is partially complete. It covers the purpose and parameters well, but lacks behavioral context (e.g., error handling, analysis output) and usage guidelines. The presence of an output schema means return values are documented elsewhere, so the description doesn't need to explain them, but overall gaps in transparency and guidelines reduce completeness.
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 description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains that 'document_path' supports 'absolute, relative, and ~ expansion', clarifying usage beyond the schema's generic 'string' type, and defines 'validation_level' options ('STRICT', 'NORMAL', 'PERMISSIVE') with a default implied by 'NORMAL' in the schema. This compensates well for the low schema coverage, though it doesn't detail what each validation level means.
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's purpose with specific verbs ('load and analyze') and resource ('Markdown document from a file path'), distinguishing it from siblings like 'get_document' (which likely retrieves without analysis) or 'analyze_document' (which may analyze without loading). However, it doesn't explicitly differentiate from 'get_document' in terms of loading vs. retrieving, 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?
The description provides no guidance on when to use this tool versus alternatives like 'get_document' or 'analyze_document'. It mentions loading and analyzing, but doesn't specify prerequisites (e.g., file existence), exclusions, or comparative contexts with sibling tools, leaving the agent to infer usage scenarios.
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 mentions validation purposes and backup behavior, which adds useful context. However, it lacks details on permissions needed, error handling, rate limits, or what happens if validation fails. The description doesn't contradict any annotations (none 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?
The description is well-structured and front-loaded: the first sentence states the purpose and context, followed by a clear Args section. Every sentence earns its place with no wasted words. It's appropriately sized for a 4-parameter 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?
Given the tool has an output schema (not shown here), the description doesn't need to explain return values. It covers the purpose, usage context, and parameter semantics adequately. However, as a mutation tool with no annotations, it could benefit from more behavioral details like error conditions or side effects.
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 description coverage is 0%, so the description must compensate. It provides clear explanations for all 4 parameters: 'document_path' (source), 'target_path' (save destination), 'backup' (create backup), and 'validation_level' (strictness with enum values). This adds significant meaning beyond the bare schema, though it could elaborate on default behaviors.
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 verb ('Save') and resource ('the document'), and specifies it's 'mainly for validation purposes since auto_save handles most cases.' This distinguishes it from simple save operations. However, it doesn't explicitly differentiate from sibling tools like 'update_section' or 'move_section' in terms of scope.
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: 'mainly for validation purposes since auto_save handles most cases.' This gives guidance on when to use this tool (for validation) versus relying on auto-save. However, it doesn't explicitly mention alternatives among sibling tools 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.

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