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spawn_asset_search

Search the local asset bank to reuse proven assets, avoid bad paths, and filter by category, kind, style, or reuse count across games.

Instructions

Search the local asset bank for assets you (or your other projects) have already used. Call this BEFORE inventing a new cdn/ asset name: a path that already produced good art is reusable across games verbatim, and a path marked bad tells you what not to spell. Every result reports how many distinct GAMES use it — the strongest signal that an asset actually worked. Pass facets:true with no query to see what categories, kinds and style families the bank holds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
nameNoExact bank name you assigned with spawn_asset_note.
slugNoMoodboard style family without the prefix, e.g. "gothic-horror".
limitNo
queryNoFree text over name, path, category, tags and description, e.g. "knight" or "mud texture".
facetsNoInclude counts by category, kind, style family and namespace over the whole match set.
prefixNoFirst token of the FILENAME, e.g. "model", "texture", "sfx". Derived from the path, not assigned by you.
projectNoOnly assets used in this project directory.
verdictNo"good" for names known to have worked, "bad" for names to avoid.
categoryNoExact category you assigned, e.g. "enemies". Use facets:true to list what exists.
minGamesNoOnly assets reused in at least this many distinct games — proven-good filter.
namespaceNomoodboard = the documented namespaced form; root = bare global names; ingested = opaque uploads.
variantIdNoOnly assets used by this game.
Behavior4/5

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

With no annotations provided, the description carries the transparency burden. It discloses result semantics ('Every result reports how many distinct GAMES use it'), the meaning of good/bad paths, and the facets behavior. It stops short of explicitly stating side effects or output shape, but 'search' implies read-only and the added detail exceeds a bare description.

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?

Four sentences, each carrying distinct value: purpose, when-to-use, result interpretation, and advanced facet exploration. It is front-loaded with the main purpose and contains no redundancy or filler. Efficient for the tool's complexity.

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 13 parameters, no required fields, and no output schema, the description covers the crucial workflow context well: when to call, how to reuse paths, how to judge signals, and how to browse facets. It doesn't enumerate return fields (e.g., pagination or limit behavior), but the rich input schema compensates, making this a strong, near-complete description.

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?

Schema description coverage is high (85%+), so baseline is 3. The description adds extra meaning for key parameters: it explains the `facets` usage pattern, ties result game-count to `minGames` filtering, and links 'bad' verdicts to spelling pitfalls. This supplements the schema descriptions meaningfully.

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 opens with a specific verb+resource ('Search the local asset bank') and clearly defines the scope ('assets you (or your other projects) have already used'). It also differentiates from siblings by emphasizing 'search' versus scan/sync/note, and by connecting to the workflow of reusing verified assets.

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

Usage Guidelines5/5

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

It gives explicit when-to-use guidance: 'Call this BEFORE inventing a new cdn/ asset name'. It also provides a concrete alternate usage ('Pass facets:true with no query to see what categories, kinds and style families the bank holds') and explains how to interpret results (distinct GAMES usage count, good/bad paths). This is actionable and unambiguous.

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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