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retail_media_esg_compliance

Read-onlyIdempotent

Audits retail media networks for ESG compliance by analyzing ad placements, tracking cookies, and verifying ethical advertising standards. Designed for ad_revenue_ops teams to ensure GDPR and sustainability compliance across digital retail platforms. Accepts domain lists or network identifiers as input and returns structured compliance reports with warnings and source references. Requires async:true to avoid timeout errors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
domainsNoList of retail media network domains to audit
checkESGNoEnable ESG advertising standards compliance check
checkGDPRNoEnable GDPR cookie tracking compliance check
networkIdsNoList of retail media network identifiers

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
summaryNo
warningsNo

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, indicating safe, non-destructive behavior. The description adds that the tool returns structured compliance reports with warnings and source references, and crucially warns about the need for async:true to avoid timeout errors. This additional context about execution requirements enhances transparency beyond what annotations provide.

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 three sentences long, front-loading the core purpose and then providing input/output details and an important execution requirement. Every sentence adds value with no redundant or vague phrasing.

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

Completeness4/5

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

Given the presence of an output schema and full parameter documentation, the description covers the essential aspects: input types, async requirement, output nature (compliance reports with warnings and source references), and target audience. However, it omits potential constraints like rate limits or maximum input sizes for domain lists, which could be relevant for an agent.

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

Parameters5/5

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

Schema description coverage is 100%, but the description adds significant semantic value by stating it accepts domain lists or network identifiers, aligning with the 'domains' and 'networkIds' parameters. It also explicitly requires async:true, which is critical for this tool's execution and not indicated in the schema description for the async parameter.

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 audits retail media networks for ESG compliance by analyzing ad placements, tracking cookies, and verifying ethical advertising standards. It specifies the output type and target audience (ad_revenue_ops teams). However, it does not explicitly distinguish this tool from sibling ESG audit tools like 'esg_audit_multi' or 'manufacturing_esg_compliance_mapper', relying on the 'retail media' context for differentiation.

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 mentions the tool is designed for ad_revenue_ops teams and requires async:true to avoid timeouts. It also states it accepts domain lists or network identifiers. However, it lacks explicit guidance on when to use this tool versus alternatives, such as other ESG compliance tools or audit tools for different domains.

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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TDQS

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

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