search_lessonsSearch TheWholeTorah.ai for lessons on a topic, across Mishnah, Tanya, Hayom Yom and Chassidus. Returns titles, links and short excerpts. Use this first to find what exists, then get_lesson for one.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many results (1-10, default 5). | |
| query | Yes | What to look for, in any language. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With readOnlyHint=true, the safety profile is already covered by annotations. The description adds useful behavioral context beyond that: it returns titles, links and short excerpts, and spans multiple Torah text categories, which helps set expectations for output shape and coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, each adding distinct value: action/scope, return shape, and usage sequencing. No filler or repetition of schema details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only search tool with fully described parameters and no output schema, the description covers what the tool searches, what it returns, and how to follow up. Nothing essential for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both query and limit are already documented in the input schema. The description's mention of 'in any language' is effectively redundant with the schema's query description, so it adds little parameter-level meaning beyond the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Search'), names the resource (TheWholeTorah.ai), and defines scope (lessons across Mishnah, Tanya, Hayom Yom and Chassidus). It also references get_lesson, distinguishing discovery from retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear usage context: 'Use this first to find what exists, then get_lesson for one.' This explicitly sequences the tool against a sibling, but it does not mention when to prefer search_sources or other alternatives, so it stops short of full when/when-not guidance.
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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Each tool targets a distinct resource or action: catalog discovery, lesson search, source search, lesson retrieval, text retrieval, audio retrieval, daily entry, and Q&A. The two search tools are explicitly separated by corpus (site lessons vs classical sources), and ask is distinct from search by returning grounded answers with citations.
Seven tools follow a clean verb_noun snake_case pattern (search_lessons, get_source_text, list_books, etc.). The single tool named 'ask' is a minor deviation from the verb_noun convention, but it is short and understandable.
Eight tools is well-scoped for a Torah learning library. Each tool has a distinct job, and there is no redundant or filler surface.
The surface covers discovery (list_books), searching (search_lessons, search_sources), retrieval (get_lesson, get_source_text, get_audio, get_daily), and synthesis (ask). This is a read-only content domain, so CRUD operations are not expected; no obvious dead ends remain.