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anon_detect_pii

Detect PII fields in database schemas and data models to ensure compliance with GDPR, CCPA, HIPAA, or PCI-DSS regulations.

Instructions

Detect PII fields in database schemas and data models

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoAPI key for authentication
regulationsNoCompliance regulations to check against
schema_sourceYesSchema definition, model code, or table DDL to scan for PII
Behavior2/5

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

With no annotations provided, the description carries the full behavioral disclosure burden, yet it only states a bare verb phrase. It does not disclose whether the operation is read-only, whether an api_key is required for every call, how the regulations parameter changes detection logic, or what the result looks like — all material for a scanning tool.

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?

A single 10-word sentence with the verb front-loaded and zero filler. It is appropriately sized for a simple detection tool, though it also misses the opportunity to pack the same brevity into richer content.

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?

The tool has no output schema, no annotations, and no usage context, leaving the description as the only behavioral channel. It does not explain the output format of detected PII fields, the effect of selecting multiple regulations, or how this differs from sibling PII scanners — gaps that matter for correct invokation.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents api_key, regulations, and schema_source adequately. The description loosely maps to schema_source ('database schemas and data models') and hints at the regulations dimension, but adds no syntactic or semantic detail beyond what the schema provides, keeping it at the baseline.

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 uses a specific verb ('Detect') with a clear resource ('PII fields in database schemas and data models'), so an agent can grasp the core function immediately. However, it does not differentiate from the closely related sibling gdpr_scan_pii, which overlaps significantly in purpose.

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 given on when to use this tool versus alternatives such as gdpr_scan_pii, pci_scan_codebase, or anon_generate_rules. The regulations parameter implies compliance-driven use cases, but the description never states a condition or context for invocation.

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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