Skip to main content
Glama

Aident AI

by ai.aident.loadout

capabilities_feedback

Report feedback about capability usage or capability search quality. Use targetType="capability" after using a capability to rate performance, reliability, correctness, latency, auth friction, or execution problems. Also use it for unclear instructions, missing schemas, or stale metadata on a specific capability. Use targetType="search" when the search results were irrelevant, incomplete, duplicated, or poorly ranked.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsNoFeedback quality or issue tags.
ratingNoOptional quality rating, especially for capability usage feedback.
commentNoShort explanation of what was wrong or useful.
surfaceNoOptional caller surface such as codex or claude-code.
targetTypeYesWhether feedback targets a capability usage/details experience or a search result set.
searchQueryNoSearch query when targetType="search".
capabilityIdNoCapability id/name when targetType="capability".
agentSessionIdNoOptional session id for external callers.
capabilityTypeNoCapability type when targetType="capability".
searchResultIdsNoOptional capability ids returned by the problematic search.

TDQS

A4.4/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint=false and destructiveHint=false, aligning with the write-but-not-destructive nature of reporting feedback. The description adds useful context about what aspects can be feedback (performance, auth friction, search quality), but does not disclose persistence or response behavior, which is acceptable given annotations.

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, front-loaded with the main purpose and then delivering targeted usage instructions for each targetType. Every sentence contributes value without redundancy.

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?

With 10 parameters and no output schema, the description covers both main use cases and specific scenarios, while the rich schema descriptions handle the remaining parameter details. It is sufficiently complete for selecting and invoking the tool, though it does not specify return values.

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 100%, so baseline is 3. The description adds conditional guidance for targetType values, clarifying when to use 'capability' versus 'search', which helps parameter selection beyond the schema's field-level descriptions.

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 clearly states 'Report feedback about capability usage or capability search quality', giving a specific verb and resource. It distinguishes two distinct target types (capability vs search), which sets it apart from sibling tools like capabilities_execute or capabilities_search.

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 explicitly instructs when to use each targetType: 'Use targetType="capability" after using a capability' and 'Use targetType="search" when the search results were irrelevant...' This provides clear contextual guidance and covers edge cases like unclear instructions or missing schemas.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Aident AI toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation5/5

Each tool owns a distinct resource/action pair (e.g., search/get/preflight/execute for capabilities, read/feedback for skills, status/connect/disconnect for vault), and detailed descriptions make boundaries explicit. No two tools appear to do the same thing, and the preflight/execute separation is clearly delineated.

Naming Consistency2/5

Naming mixes bare nouns (auth, billing, vault), prefixed subject-verb pairs (capabilities_execute, skills_feedback), and the outlier 'loadout_bug_submit' with inconsistent pluralization (capabilities vs skills vs loadout). Although all tokens are lowercase and underscore-separated, there is no single predictable pattern, and some tools (e.g., 'billing') are action containers while others are single-action functions.

Tool Count5/5

Thirteen tools is well within the ideal 3–15 range, and each tool serves a clearly separable domain (authentication, billing, capabilities, skills, vault, audit, feedback, bug reporting). No tool feels redundant, and the count is appropriate for the breadth of functionality offered.

Completeness4/5

The surface covers the full lifecycle for capabilities (search/get/preflight/execute/feedback) and handles account, billing, vault, audit, and support needs. The only gap is lack of a general skill search or listing capability—skills can only be read by exact canonical identity, which may impede discovery—but core workflows are otherwise complete.

Resources