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anon_create_script

Create a full data anonymization pipeline script for database environments. Specify ORM, database type, and target environments to generate a ready-to-run script.

Instructions

Pro: Create a full data anonymization pipeline script for database environments

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ormNoORM or raw SQLprisma
api_keyNoAPI key for authentication
databaseNoDatabase typepostgresql
environmentsNoTarget environments
Behavior2/5

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

No annotations are present, so the description carries the full behavioral burden. It only says 'Create' and gives no indication of side effects, whether it writes files, calls an API (despite an api_key parameter), or what the returned script contains.

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 a single sentence with no padding, and the core action is front-loaded. The unexplained 'Pro:' prefix is a minor blemish but doesn't materially hurt 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?

For a generator with no output schema and no annotations, the description is too sparse: no return format, no behavior, no prerequisite or effect explanation. An agent wouldn't know whether the tool emits code to chat, writes files, or requires an external service call.

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 coverage is 100% and every parameter has a description/enum/default, so the schema carries the semantic weight. The description adds only the 'full pipeline' framing and doesn't explain how parameters like api_key or environments influence the generated script.

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 identifies a concrete artifact ('full data anonymization pipeline script') and a clear action ('Create'), scoped to 'database environments.' It doesn't explicitly contrast with sibling tools like anon_detect_pii or anon_generate_rules, but the resource is specific enough that the primary purpose is unambiguous.

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 when-to-use guidance, no exclusions, and no reference to alternatives. The closest sibling tools (anon_detect_pii, anon_generate_rules) are not mentioned, so an agent gets no help choosing between detection, rule generation, and full script generation.

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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