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query_lessons

Search Younanix engineering lessons by natural language query. Returns an agent-native envelope (schema_version 2) with status, structured lessons, coded errors, and next_actions. Free preview surface — full lesson bodies require query_lessons_premium or the paid agent-query endpoint.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language search query
verbosityNocompact (default) trims lesson bodies and drops narrative prose; full returns everything.
max_resultsNoMaximum number of results to return (default 10)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
errorNo
statusYes
surfaceYes
next_actionsYes
schema_versionYes

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses the response envelope (schema_version 2, status, structured lessons, coded errors, next_actions) and the preview limitation, which is substantial. It does not mention rate limits or side effects, but read-only search tools rarely need further disclosure.

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 sentences, no fluff. The core purpose is stated immediately, followed by the return envelope and the critical limitation. Every sentence earns its place.

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?

The description is complete for a search tool: it describes the return format, error handling (coded errors), and next_actions. The output schema (per signals) further covers return structure. Only minor gaps exist, such as not explicitly stating the default max_results, but that is in the schema.

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 all parameters (query, verbosity, max_results) are fully documented in the schema. The description adds no additional parameter-level detail beyond the high-level envelope mention, which matches the baseline of 3 for high schema coverage.

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 resource (Younanix engineering lessons) and describes the output envelope. It explicitly frames itself as a 'free preview surface' and names query_lessons_premium as the full-access alternative, but does not differentiate from the sibling query_lessons_full, leaving some ambiguity about how it differs from that tool.

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?

Provides an explicit when-not: full lesson bodies require query_lessons_premium or the paid agent-query endpoint. However, it does not mention when to use query_lessons_full instead, so the guidance is incomplete for distinguishing among all siblings.

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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TDQS

B3.4/5.0
Disambiguation2/5

Most task-run and record_* tools are clearly distinct, but query_lessons, query_lessons_full, and query_lessons_premium all describe nearly the same underlying lesson-query action separated mainly by access tier and payment. An agent can easily call the wrong one, especially because 'full' and 'premium' boundaries are unclear.

Naming Consistency5/5

The tools consistently use snake_case verb_noun names such as start_task_run, complete_task_run, record_reflection, and submit_incident_report. The query_lessons variants use a predictable suffix pattern, and there is no mixing of naming conventions.

Tool Count4/5

Ten tools is a reasonable footprint, but the three query_lessons variants are essentially reimplementations of the same query by payment/access tier. The count is not excessive, though it could be reduced without losing real capability.

Completeness3/5

The set covers task-run start/completion and lesson querying, but there is no way to read back task runs, reflections, subagent traces, or usage records after submitting them. This makes the task-run side feel mostly write-only and creates a notable gap in a memory-focused server.

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