MCP PII Tools

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation3/5
There is significant functional overlap between tools, particularly mcp_encrypt_text_pii and mcp_process_text which both combine detection with another operation, and mcp_decrypt_pii_item versus mcp_decrypt_text_pii which differ in scope but share core purpose. However, the descriptions help clarify the distinctions, preventing complete confusion.
Naming Consistency5/5
All tools follow a consistent mcp_verb_noun naming pattern with snake_case throughout. The verbs (anonymize, batch_process, decrypt, detect, encrypt, process) are descriptive and uniformly applied, making the set predictable and easy to parse.
Tool Count4/5
With 8 tools, the count is reasonable for a PII processing domain, covering detection, encryption, decryption, anonymization, and batch operations. It's slightly heavy due to overlapping tools but still within a well-scoped range for the purpose.
Completeness4/5
The toolset covers core PII operations well: detection, encryption, decryption, and anonymization, with batch processing for scalability. A minor gap exists in update or delete operations for PII data, but agents can work around this with the provided tools for most workflows.
Average 2.7/5 across 8 of 8 tools scored. Lowest: 1.9/5.
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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description only states it 'processes' texts in batch and returns results, without explaining what processing entails, whether it's read-only or mutative, what permissions are needed, error handling, rate limits, or any behavioral traits. This is inadequate for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with Args and Returns sections, which is organized. However, it includes redundant elements like 'MCP Tool:' prefix and could be more front-loaded. The content is concise but under-specified - every sentence earns its place but provides insufficient information overall.
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 annotations, 0% schema description coverage, but having an output schema (Returns: Dict[str, Any]), the description is incomplete. It doesn't explain what the batch processing actually does, how it differs from siblings, what the return dictionary contains, or any behavioral aspects. For a tool with one parameter but unclear functionality among multiple siblings, this description leaves critical gaps.
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 mentions 'texts (List[str]): 처리할 텍스트 리스트' (texts to process list), which adds basic semantics about the parameter being a list of strings for processing. However, it doesn't explain constraints like minimum/maximum list size, text length limits, or content requirements. The description provides minimal parameter context beyond what the bare schema shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states '여러 텍스트 일괄 처리' (batch processing of multiple texts) which is a tautology of the tool name 'mcp_batch_process'. While it mentions the verb '처리' (process) and resource '텍스트' (texts), it doesn't specify what kind of processing occurs or how this differs from sibling tools like 'mcp_process_text'. The purpose remains vague beyond the literal translation of the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With siblings like 'mcp_process_text' (which appears to process individual texts) and various PII-related tools (anonymize, detect, encrypt, decrypt), there's no indication whether this tool is for bulk operations, specific processing types, or how it relates to other tools. The description offers zero usage 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?
No annotations are provided, so the description carries full burden. It states the tool returns anonymized text but doesn't disclose what anonymization means (masking, replacement, removal), whether it's reversible, what happens to the original text, or any performance/rate limit considerations. For a PII handling tool with zero annotation coverage, this is a significant behavioral gap.
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 concise with a clear structure: tool name, args section, and returns section. There's no unnecessary verbosity. However, the bilingual presentation (Korean title with English description) creates minor cognitive overhead, and the description could be more front-loaded with purpose before parameter documentation.
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 2 parameters with 0% schema coverage, no annotations, but an output schema exists, the description is minimally adequate. The output schema means the description doesn't need to explain return values, but it should do more to explain parameter semantics and behavioral context for a PII handling tool. It meets the bare minimum but leaves important questions unanswered.
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. It lists parameters and types but adds minimal semantic meaning. 'PII items' is documented as a list of dictionaries but the description doesn't explain what keys/values are expected, what PII types are supported, or how the tool uses these items to anonymize the text. The description doesn't adequately compensate for the schema coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'anonymizes text' which is a clear verb+resource combination, but it doesn't specify how this differs from sibling tools like mcp_process_text or mcp_batch_process. The Korean title '텍스트 익명화' translates to 'text anonymization' which restates the English name rather than adding clarity.
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 about when to use this tool versus alternatives. With sibling tools like mcp_detect_pii, mcp_encrypt_text_pii, and mcp_process_text available, the description doesn't explain whether this tool should be used before/after detection, or how it differs from encryption tools. The description only documents parameters without usage 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 states the tool decrypts PII items but doesn't cover critical aspects: what permissions or authentication are required, whether it's a read-only or mutating operation, potential rate limits, error handling, or what the decryption process entails. This leaves significant gaps in understanding the tool's behavior and constraints.
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 structured with clear sections for Args and Returns, making it easy to scan. However, the first line 'MCP Tool: PII 항목 복호화' is somewhat redundant with the tool name, and the content could be more front-loaded with critical usage information. Overall, it's efficient but not optimally organized for immediate understanding.
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 complexity (decryption operation with security implications), lack of annotations, and an output schema that only indicates a dict return, the description is incomplete. It covers basic purpose and parameters but misses behavioral context, error cases, and security considerations. The output schema helps by specifying the return type, but the description should do more to compensate for the annotation gap.
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 schema provides no parameter details. The description adds basic semantics: 'encrypted_value' is the value to decrypt, and 'pii_type' is the PII type. However, it doesn't explain valid pii_type values, encryption formats, or examples, which limits practical use. This partial compensation justifies a baseline score, but more detail would be needed for higher marks.
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 'PII 항목 복호화' (PII item decryption), which is a specific verb+resource combination. It distinguishes itself from siblings like mcp_decrypt_text_pii (text PII decryption) and mcp_encrypt_pii_item (PII item encryption), though the differentiation could be more explicit. The description doesn't fully explain what constitutes a 'PII item' versus 'text PII,' 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. It doesn't mention prerequisites (e.g., needing encrypted PII data), exclusions, or comparisons to siblings like mcp_decrypt_text_pii or mcp_encrypt_pii_item. The agent must infer usage from the tool name and context alone, which is insufficient for clear decision-making.
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 decrypts PII from encrypted text but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or whether it's a read-only or mutative operation. This is a significant gap for a tool handling sensitive PII data.
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 efficiently structured with a clear purpose statement followed by Args and Returns sections. It avoids unnecessary fluff and is appropriately sized for the tool's complexity. However, the use of Korean might reduce clarity for some agents, and the Returns section could be more descriptive.
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 complexity (handling PII decryption with two parameters and nested objects), the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral details and usage guidelines. The presence of an output schema helps, but without annotations, the description should do more to explain security implications and error cases.
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 lists both parameters (encrypted_text and encrypted_items) with brief explanations, adding some semantic value beyond the schema's 0% description coverage. However, it doesn't fully compensate for the coverage gap—details like the format of encrypted_items mapping or examples are missing. The baseline is 3 since it provides basic parameter context.
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: '암호화된 텍스트에서 PII 복호화' (Decrypt PII from encrypted text). It specifies both the verb (decrypt) and the resource (PII from encrypted text), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like mcp_decrypt_pii_item, which might handle individual items rather than text.
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. It doesn't mention sibling tools like mcp_decrypt_pii_item or mcp_anonymize_text, nor does it specify prerequisites or contexts for usage. This leaves the agent without clear direction on 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool detects PII but doesn't specify what types of PII are detected (e.g., names, emails, SSNs), the detection method (e.g., regex, ML models), or any limitations (e.g., accuracy, language support). This leaves significant gaps in understanding how the tool behaves beyond its basic function.
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 structured with clear sections for Args and Returns, making it easy to parse. However, the title is null, and the content could be more front-loaded with the core purpose before parameter details. It avoids redundancy but misses opportunities for efficiency in explaining behavior.
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 complexity (PII detection can involve nuanced logic), lack of annotations, and presence of an output schema, the description is minimally adequate. It covers the basic function and parameters but fails to address key behavioral aspects like detection scope or error handling. The output schema likely details the return structure, reducing the need for return value explanation, but overall completeness is limited.
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 adds minimal value beyond the input schema. It documents the single parameter 'text' as '분석할 텍스트' (text to analyze), which aligns with the schema's 'Text' title but doesn't provide additional context like format expectations (e.g., plain text vs. structured data) or constraints (e.g., length limits). With 0% schema description coverage, this is inadequate compensation, but the single parameter keeps it from being lower.
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: '텍스트에서 PII 탐지' (Detect PII in text). It specifies the verb (detect) and resource (PII in text), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like mcp_anonymize_text or mcp_process_text, which likely perform related but distinct operations.
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 mcp_anonymize_text (which might anonymize PII after detection) and mcp_process_text (a more general tool), the agent lacks explicit direction on selection criteria, such as 'use this for detection only' or 'combine with mcp_anonymize_text for full anonymization.'
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 the tool encrypts PII items but lacks details on encryption method, security implications, permissions required, rate limits, or error handling. For a tool handling sensitive data with zero annotation coverage, 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 with the tool's purpose. It uses a structured format with Args and Returns sections, which is efficient. However, the inclusion of 'MCP Tool:' is redundant, and the content could be more streamlined without losing 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 the tool's complexity (handling sensitive PII data), lack of annotations, and presence of an output schema, the description is moderately complete. It covers basic purpose and parameters but misses critical behavioral details like security and error handling. The output schema likely documents return values, reducing the need for description here, but overall completeness is adequate with clear gaps.
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 basic semantics by explaining pii_value as '암호화할 PII 값' (PII value to encrypt) and pii_type as 'PII 유형 (이름, 전화번호, 이메일 등)' (PII type like name, phone number, email). However, it does not specify format constraints, examples, or validation rules, leaving parameters partially documented.
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 'PII 항목 암호화' (PII item encryption), which specifies both the verb (encrypt) and resource (PII item). It distinguishes from siblings like mcp_encrypt_text_pii (which encrypts text PII) by focusing on individual PII items, though the distinction could be more explicit. The purpose is specific and actionable.
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. It does not mention siblings like mcp_encrypt_text_pii (for text PII) or mcp_anonymize_text (for anonymization), nor does it specify prerequisites or exclusions. Usage is implied by the tool name and description alone, leaving the agent to infer 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?
No annotations are provided, so the description carries the full burden. It mentions detection and encryption but lacks critical behavioral details: what types of PII are detected, the encryption method used, whether the operation is reversible (hinted by 'mcp_decrypt_text_pii' sibling), performance characteristics, or error handling. This is inadequate for a mutation tool with zero annotation 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?
The description is concise and well-structured: it starts with the tool's purpose, lists the single argument with a brief explanation, and notes the return type. There's no unnecessary information, and it's front-loaded with the core functionality. However, the lack of usage context or behavioral details slightly limits its effectiveness.
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 (detection and encryption), no annotations, and an output schema (which handles return values), the description is partially complete. It covers the basic purpose and parameter but misses usage guidelines, behavioral transparency, and differentiation from siblings. This makes it minimally viable but insufficient for optimal agent decision-making.
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 adds minimal semantics beyond the input schema. It states 'text (str): 처리할 텍스트' (text to process), which slightly clarifies the parameter's purpose but doesn't provide format constraints, length limits, or examples. With 0% schema description coverage and only one parameter, this is a baseline score—adequate but with clear gaps in detailed guidance.
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: '텍스트에서 PII를 탐지하고 암호화' (detect and encrypt PII in text). It specifies both the action (detect and encrypt) and the resource (text with PII). However, it doesn't explicitly differentiate from sibling tools like 'mcp_detect_pii' (detection only) or 'mcp_encrypt_pii_item' (encrypts individual PII items), which prevents 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 Guidelines2/5
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 'mcp_detect_pii' (detection only), 'mcp_encrypt_pii_item' (encrypts individual items), and 'mcp_anonymize_text' (anonymization), there's no indication of the specific use cases, prerequisites, or trade-offs for choosing this combined detection+encryption tool over others.
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. While it mentions '탐지 + 익명화' (detection + anonymization), it doesn't specify what types of PII are detected, how anonymization is performed (masking, replacement, etc.), whether the operation is reversible, what permissions are required, or any rate limits. For a PII processing tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
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 efficiently structured with clear sections for the tool name, arguments, and returns. Each sentence serves a purpose: stating the function, documenting the parameter, and indicating the return type. However, the mixed Korean/English formatting could be slightly cleaner, and the 'MCP Tool:' prefix is somewhat redundant given the context.
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 this is a PII processing tool with no annotations but with an output schema (indicated by 'Has output schema: true'), the description is minimally adequate. It covers the basic purpose and parameter, and the output schema will handle return value documentation. However, for a sensitive operation like PII processing, more context about what constitutes PII, how anonymization works, and security considerations would be valuable.
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 the single parameter 'text' with its type and purpose ('처리할 텍스트' meaning 'text to process'). With 0% schema description coverage, this adds crucial semantic meaning beyond the bare schema. However, it doesn't provide additional context about text length limits, supported languages, or formatting requirements that would be helpful for proper 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 tool's purpose: '텍스트 PII 처리 (탐지 + 익명화)' which translates to 'Text PII processing (detection + anonymization)'. This specifies the verb (process), resource (text), and scope (PII detection and anonymization). However, it doesn't explicitly distinguish this from sibling tools like 'mcp_detect_pii' or 'mcp_anonymize_text', which appear to offer separate detection or anonymization functions.
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 sibling tools like 'mcp_detect_pii' and 'mcp_anonymize_text' available, there's no indication whether this tool should be used for combined detection+anonymization workflows, or how it differs from using those tools separately. No context about prerequisites, limitations, or appropriate scenarios is provided.
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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