Aident AI

Send action feedback to Aident

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

Name	Required	Description
`tags`	No	Feedback quality or issue tags.
`rating`	No	Optional quality rating, especially for capability usage feedback.
`comment`	No	Short explanation of what was wrong or useful.
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`surface`	No	Optional caller surface such as codex or claude-code.
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`targetType`	Yes	Whether feedback targets a capability usage/details experience or a search result set.
`searchQuery`	No	Search query when targetType="search".
`capabilityId`	No	Capability id/name when targetType="capability".
`agentSessionId`	No	Optional session id for external callers.
`capabilityType`	No	Capability type when targetType="capability".
`searchResultIds`	No	Optional capability ids returned by the problematic search.

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedSep 14, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / context

Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "targetType"
-]New value: +[
+  "targetType",
+  "context",
+  "llm_model"
+]

First observedAug 7, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations declare readOnlyHint=false, destructiveHint=false, openWorldHint=false, so the agent already knows this is a non-destructive write. The description is consistent with that profile but adds little behavioral detail beyond it – no mention of whether feedback is queued, acknowledged, or has any side effect visible to the user.

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?

Three sentences, no filler, and the routing guidance is front-loaded: sentence one sets purpose, sentence two covers targetType=capability, sentence three covers targetType=search. Tight and scannable.

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?

For a 12-parameter submission tool with 100% schema description coverage and no output schema, the description covers the key agent decision (which targetType and what to report). Nothing essential to calling it correctly is missing, though the analytics-only nature of some fields is only conveyed via the schema.

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 coverage is 100%, so all 12 parameters are already documented. The description nevertheless adds real meaning by explaining what each targetType value is meant to capture, exceeding the schema's terse enum description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (report feedback) and resource (capability usage or capability search quality), and the two targetType modes make the scope concrete. It does not differentiate itself from the sibling skills_feedback, leaving a similar-sounding tool's relationship unresolved.

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 explicit when-to-use conditions for each targetType value: rate a capability after use for performance/reliability/latency/etc., and report irrelevant/incomplete/duplicated/poorly-ranked search results. It stops short of naming alternatives (skills_feedback, loadout_bug_submit) or when-not to use it, so routing against siblings is left to inference.

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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