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audit_data_integrity

Audits Roblox data stores and receipt flows for session, pcall, persistence, yield, and grant-order safety vulnerabilities.

Instructions

Audits ProfileStore/ProfileService/DataStore and receipt flows for session, pcall, persistence, yield, and grant-order safety.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sideNoExecution-side filter.
queryNoOptional script name/path filter.
offsetNoZero-based script offset.
max_scriptsNoMaximum live scripts to audit.
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 does not state whether the audit is read-only, what side effects might occur, what the output format is, or any performance/rate-limit implications. The description is too terse to convey the tool's behavior beyond its stated purpose.

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 a single concise sentence that front-loads the verb and immediately communicates scope. There is no redundancy or filler. Every word contributes to explaining the tool's focus.

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 is an audit tool with no output schema, so the description should explain what the audit returns or produces. It does not. It also lacks guidance on how to use the parameters (e.g., what 'side' affects) or any disambiguation from sibling audit tools. This leaves significant gaps for an agent to invoke it correctly.

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 input schema covers all four parameters with clear descriptions (side enum, query, offset, max_scripts), achieving 100% schema_description_coverage. The description adds no parameter-specific details, but since the schema fully documents them, 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.

Purpose5/5

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

The description clearly states the verb 'Audits' and specifies the exact resources (ProfileStore/ProfileService/DataStore, receipt flows) and the safety properties checked (session, pcall, persistence, yield, grant-order). This level of specificity distinguishes it from sibling audit tools like audit_lifecycle or audit_performance.

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

Usage Guidelines3/5

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

The description implies usage for integrity checks on specific systems and flows, but does not explicitly state when to choose this tool over alternatives or provide exclusions. No mention of prerequisites or scenarios. This is implied rather than explicit guidance, so it only meets the baseline.

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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