askAsk a question and get an answer grounded ONLY in TheWholeTorah.ai's own lessons and sources, with citations. It will say when it does not know rather than guess. Prefer this for 'what does X say about Y' questions.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Answer language: en, he, es, fr, ru, yi. Default en. | |
| question | Yes | The question, 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?
Even with readOnlyHint=true already declared, the description adds meaningful behavioral context: answers are grounded exclusively in internal lessons/sources, citations are included, and the tool will state when it does not know rather than guess. This goes beyond what annotations provide.
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 tight sentences: the first states the core function and grounding constraint, the second discloses the honesty behavior, and the third gives a usage cue. No redundant wording; every sentence earns its place.
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?
With no output schema, the description covers the key expectations: an answer with citations, grounding limits, and refusal to guess. Combined with parameter documentation, an agent has enough to invoke the tool correctly. A slightly fuller description of output format would push this to 5, but it is not a significant gap.
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%, and the schema already explains both parameters clearly. The description does not add new parameter-level semantics beyond what the schema states, so the baseline of 3 is appropriate.
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 clearly states the verb ('ask'), the resource (a grounded Torah question), and the unique behavior: answers are grounded ONLY in TheWholeTorah.ai's own lessons and sources, with citations. This distinguishes it from the sibling retrieval/search tools without requiring the agent to open their schemas.
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 explicitly recommends this tool for 'what does X say about Y' questions, giving the agent a clear selection heuristic. It stops short of naming specific when-not-to-use cases or alternative tools, but the preference signal is strong and actionable.
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.