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Heista

by co.heista

Get Saved Assets (Batch)

get_saved_assets_batch
Read-onlyIdempotent

Fetch up to 50 saved assets by id in one round-trip. Use when an agent needs to pull a pre-selected set — e.g. resolving a saved_asset_picker context input on a Heist that requires N pinned assets. Missing or cross-workspace ids are silently dropped; compare returned items vs requested ids to detect drops.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asset_idsYesUp to 50 asset ids to fetch in one round-trip. Use when an agent needs to pull a pre-selected set of saves (e.g. resolving a saved_asset_picker declaration in a Heist). Missing/cross-workspace ids are silently dropped.

TDQS

A4.3/5.0
Behavior4/5

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

Adds behavioral details beyond annotations: batch size limit (50) and silent dropping of missing/cross-workspace ids. Annotations already declare readOnlyHint=true and idempotentHint=true.

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?

Two sentences with no extraneous words. First sentence states core function; second sentence provides use case and important behavioral note.

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 single parameter and good annotations, the description fully covers the tool's behavior, including limit, silent drops, and guidance on handling missing IDs. No output schema needed as returns are standard.

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%, but the schema description is nearly identical to the tool description. The description does not add additional meaning beyond the schema baseline.

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?

Clearly states verb 'fetch', resource 'saved assets', and constraints 'by id in one round-trip'. Distinguishes from siblings like get_saved_asset and list_saved_assets by specifying batch size and ID-based retrieval.

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?

Provides explicit use case: 'resolving a saved_asset_picker context input on a Heist'. Implies when not to use by contrasting with alternatives (get_saved_asset for single, list_saved_assets for listing). Lacks explicit 'do not use when', but context suffices.

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