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evaluate_pose_search_query

Read-onlyIdempotent

Diagnose null chooser results by running a live motion-matching query against a UPoseSearchDatabase, returning the best-match asset and search cost.

Instructions

Run a live motion-matching query on a PIE/Game actor against a loaded UPoseSearchDatabase (UPoseSearchLibrary::MotionMatch) and return the best-match asset + search cost, plus the query trajectory. Diagnoses why a chooser returns null. Best-effort: per-channel cost is not exposed by the BlueprintPure result.

Returns: { world_mode, actor_name, actor_resolved, anim_instance_class, pose_history_name, pose_history_found, database_path, query_trajectory_samples[], trajectory_sample_count, is_trajectory_empty, has_match, best_match_asset, best_match_database, best_cost, selected_time, is_continuing_pose_search, wanted_play_rate, is_mirrored, is_looping, per_channel_cost[], note, world_name, world_package, world_type, net_mode, pie_instance }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
worldNoWhich world to resolve: absent (default) = prefer the live PIE/Game world | 'server' (the PIE world with authority) | 'client' | 'pie:N' | 'pie'/'game' force the live session (errors if none running) | 'editor' forces the editor world.
actor_nameNoActor name or label whose AnimInstance drives the query. Omitted = the first player controller's pawn.
database_pathYesUPoseSearchDatabase asset path to search (required).
pose_history_nameNoTag of the PoseSearchHistoryCollector anim-graph node used to build the query (default 'PoseHistory').
max_trajectory_samplesNoCap on emitted query trajectory samples (<=0 = all; default 0).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds real behavioral context beyond that: it is best-effort because 'per-channel cost is not exposed by the BlueprintPure result', and it requires a live PIE/Game actor. That limitation disclosure is exactly the kind of extra context annotations cannot convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first sentence, followed by diagnostic intent and the best-effort caveat. The long return-field list is dense but justified because there is no output schema, so it earns its place; only minor tightening is possible.

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?

With no output schema, the description fully enumerates the return payload (world_mode, has_match, best_match_asset, best_cost, trajectory fields, etc.), which is essential here. Combined with the runtime precondition and the limitation note, an agent has everything needed to invoke and interpret the tool.

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%, so the schema already documents world, actor_name, database_path, pose_history_name, and max_trajectory_samples. The description adds no parameter-level syntax or default detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('Run a live motion-matching query on a PIE/Game actor against a loaded UPoseSearchDatabase') and cites the underlying API (UPoseSearchLibrary::MotionMatch). This clearly distinguishes it from asset-inspection siblings like inspect_pose_search_database and from the chooser-table evaluate_* tools, so an agent can pick it without opening the schema.

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?

Gives a clear use context ('live ... on a PIE/Game actor') and a purpose ('Diagnoses why a chooser returns null'), which tells the agent when this tool applies. It stops short of naming an alternative or stating when NOT to use it (e.g., against a non-running session), so it falls just below the top band.

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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