Aident AI

Search Aident Skills

skills_search

Read-only

Search Aident-curated public text Skills. Results contain contextual snippets only; call skills_read to pick a result and load its full entrypoint.

Input Schema

Name	Required	Description
`sort`	No
`tags`	No
`limit`	No
`query`	Yes
`cursor`	No
`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."
`category`	No	Category returned by skills_search
`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.
`referencedCapabilityNames`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed5 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 / properties / sort / enum

Previous value: -[
-  "relevance",
-  "popular"
-]New value: +[
+  "relevance",
+  "popular",
+  "favorites",
+  "views"
+]

changedInput schema / required

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

AddedSep 7, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, covering the safety profile. The description adds a genuinely useful behavioral fact beyond annotations: results are contextual snippets only and require a follow-up skills_read. It omits pagination behavior (the cursor param) that would help an agent loop correctly.

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 tight sentences, front-loaded with the core purpose and then the critical follow-up constraint. Every clause earns its place with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema the description can legitimately skip return-value detail, and it correctly flags the snippet-only nature of results. But for a 9-parameter tool with 33% schema coverage, it leaves pagination, sorting, and tag/category filtering entirely unexplained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33%, so the description should compensate for undocumented params (sort, tags, category, cursor, limit, referencedCapabilityNames). It adds no parameter meaning whatsoever, and with low coverage the schema cannot carry the burden alone.

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 (search) and a scoped resource (Aident-curated public text Skills), distinct from skills_read and skills_feedback. It does not, however, contrast itself against other search tools like capabilities_search, so sibling differentiation is only partial.

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

Usage Guidelines3/5

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

The second sentence describes the workflow: results are snippets, and skills_read must be called to load a full entrypoint. That implies search-then-read usage but gives no explicit condition for choosing this tool over capabilities_search or when not to use it.

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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