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Heista

by co.heista

Reclassify Brand Assets

reclassify_brand_assets

Batch re-run the vision tagger against every asset in a brand that hasn't been reviewed yet (vision_classified=false). Recovers rows the scan-time tagger dropped because of CDN blocks (Shopify hotlink, Cloudflare bot gates) or transient failures. Skips videos and rows already marked not_asset. Processes up to 24 assets per call — if more remain, the response returns { remaining > 0 } and the caller can invoke again. Paid (batched vision tag credit, typically < $0.01 per invocation).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brand_idYesBrand whose unreviewed assets should be re-run through the vision tagger. Only assets with vision_classified=false are processed. Get from list_brands.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint=false, destructiveHint=false), the description discloses cost (<$0.01 per invocation), batching limit (24 assets), retry logic (remaining>0), and exclusions. It also explains the recovery mechanism, providing full transparency for an agent to make informed decisions.

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 concise (under 100 words) and well-structured, front-loading the main action and then providing critical details (skips, limits, cost). Every sentence serves a purpose without redundancy.

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

Completeness5/5

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

Given the tool's complexity (batch processing, filtering, cost, batching limit), the description covers all necessary aspects. It even describes the response format despite no output schema, making it self-contained for an agent.

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

Parameters4/5

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

The sole parameter 'brand_id' is fully described in the schema (100% coverage). The description adds practical guidance ('Get from list_brands') and clarifies the context ('Only assets with vision_classified=false'), adding value beyond the schema's type and format.

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 uses specific verbs ('Batch re-run') and clearly identifies the resource ('vision tagger against every asset in a brand'), with conditions and exclusions that distinguish it from similar tools like 'retag_brand_asset'. It explicitly states the scope and purpose.

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

Usage Guidelines4/5

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

The description explains when to use (for assets dropped due to CDN blocks or transient failures) and what is skipped (videos and not_asset rows). It also details batching behavior and cost, but does not explicitly state alternative tools for different scenarios, though the context of batching vs. individual retagging is implied.

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

A3.7/5.0
Disambiguation4/5

Despite the high tool count, most tools have distinct purposes with thorough descriptions that specify when to use each. Some overlap exists among creative direction tools (call_creative_worlds vs chat_with_creative_worlds), but the descriptions clarify usage patterns.

Naming Consistency3/5

Naming conventions are inconsistent overall: some follow verb_noun (create_powersource_url, decode_ad), others use noun_verb or compound names (adformula_intelligence, fleet_analytics_overview). However, subgroups like dispatch_* and list_*_presets maintain internal consistency.

Tool Count2/5

112 tools is far beyond the typical 3-15 range for well-scoped servers. While the server covers a broad domain, the sheer number likely overwhelms agents and suggests insufficient consolidation of related operations.

Completeness4/5

The tool set covers core creative intelligence workflows: brand analysis, ad decoding, script generation, creative direction, and research. Minor gaps exist (e.g., no social media publishing tools), but the main use cases are well-supported.

Resources