Data Compliance Classifier MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It reveals what the tool returns (specific regulation, problematic fields, redaction strategy, compliant reformulation) and the consequence of not using it (unremediated violation with no audit trail). This is transparent about both the output and the importance of invoking the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose and repetitive. It states the purpose, then repeats the trigger condition ('immediately after validate_data_safety returns...' vs. 'Use this when validate_data_safety has returned...') and the output details ('Retrieves... report and remediation strategy' vs. 'Returns the specific regulation triggered...'). This redundancy makes the description longer than necessary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is quite comprehensive for a tool with 6 parameters and an output schema. It covers when to use it and what it returns, and adds the critical behavioral warning about audit trail. It does not elaborate on mode specifics or error handling, but the schema covers modes and the output schema covers return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema descriptions cover 100% of the parameters, including the mode enum and payload requirements. The description does not add parameter-level semantics beyond the schema, so the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'Retrieves a detailed compliance report and remediation strategy for a flagged payload' and explicitly distinguishes it from sibling validate_data_safety by specifying that it is used after a non-SAFE verdict. The verb+resource is specific and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance: 'Call this BEFORE your agent decides whether to proceed, redact, or halt -- immediately after validate_data_safety returns REDACT_BEFORE_PASSING, DO_NOT_STORE, or ESCALATE.' It also gives a strong directive: 'Do not proceed with the original payload after a non-SAFE verdict without running this tool first.' This clearly defines the trigger and required action.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does so admirably: it discloses in-memory processing and immediate discarding ('never stored or logged'), spells out the four possible verdicts, and warns about regulatory exposure for unclassified sensitive data. It also clarifies the output is machine-ready and requires no further analysis.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is longer than average but each sentence contributes: purpose, timing, verdict list, warning, and next step. It is well-structured with the main action first, though the enumeration of specific payment services adds minor verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple regulatory frameworks, verdicts), the description covers the key aspects: when to call, what it validates, what it returns, and the follow-up action. The presence of an output schema covers return-value details, so no additional explanation is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All four parameters have descriptions in the schema (100% coverage), so the baseline is 3. The description adds only the note that payload is discarded and that context improves verdict accuracy, but it doesn't elaborate on individual parameter semantics beyond the schema. Thus no uplift above baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb 'Validates' and resource 'data payload' against named frameworks (GDPR, HIPAA, PCI-DSS), making the tool's function unambiguous. It mentions the follow-up get_safety_report and implies a full version versus the lite sibling, but does not explicitly differentiate from validate_data_safety_lite, so it misses the full 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit timing guidance ('Call this BEFORE your agent passes any assembled payload to an external API, writes it to a database, or transmits it via any third-party service') and defines the exact moment to use it. It also instructs the agent to call get_safety_report next when the verdict is not SAFE_TO_PROCESS, providing clear next-step guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 performance ('under 100ms'), scope ('no AI, no IP check, no jurisdiction lookup'), and limitations (warns about contextual PII and non-standard credential formats slipping through). This is exemplary transparency that goes well beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured: it opens with the core purpose, then usage, then limitations, with no wasted words. Every sentence conveys essential information, and the warnings about misuse are concise but impactful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description fully covers the tool's purpose, usage, alternatives, performance characteristics, and limitations. Given the output schema exists and the description is this rich, the agent has everything needed to decide when and how to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with clear descriptions for both 'payload' and 'context'. The tool description does not add new parameter-level semantics beyond what the schema already provides, but it neither contradicts nor confuses them, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'validates a payload for sensitive patterns without AI classification', specifying the verb, resource, and method. It distinguishes itself from the sibling 'validate_data_safety' by emphasizing it is a fast, pattern-only filter, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit usage guidance: 'Call this BEFORE pre-screening high-volume payloads' and 'Use to filter large batches before selectively running validate_data_safety on flagged payloads'. It also gives a clear exclusion: 'Do not use as a substitute for validate_data_safety before storing or transmitting data in regulated environments', naming the alternative and when to avoid this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.