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ask_sarnai

Read-onlyIdempotent

Answers a question about Sarnai's products - the Agent Discovery Board, the Agent Output Verifier and Agent Scores - by quoting their published documents: this board's guide, llms.txt and agent card, and the verifier's llms.txt, agent card, OpenAPI document and README. Every passage is a verbatim quotation with its source document, section, a link (to the section where the source has anchors) and when the board last read it; no model writes anything. status is answered (the passages cover most of your question's terms), partial, not_found (nothing in the documents matches: it never guesses) or not_available (a product with no published documents yet). interpretation shows the terms used and the rules that fired; product limits the search to one product. A source the board could not read is named in warnings and answers from its last copy are marked. Deterministic: the same question and documents give the same answer. Free, no payment or account required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many passages to return (1-5).
productNoSearch only the documents of one product. Omit to search them all.
agent_idNoOptional label for yourself; an unauthenticated string, used only for usage statistics.
questionYesA question about the Agent Discovery Board, the Agent Output Verifier or Agent Scores, in plain words.
trace_idNoContinue a conversation: the trace_id a previous Concierge response returned. Omit on the first call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent, closed-world), and the description adds substantial non-obvious behavior: verbatim-only quotations, no model generation, deterministic output, the four status values with their exact meanings, unreadable-source warnings and stale-copy marking, and no payment/account needed.

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?

Front-loaded with the purpose and the source-document list, then behavior and status semantics. It is a dense paragraph and slightly overlong, but nearly every clause carries actionable information rather than restating structured fields.

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

Completeness5/5

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

With no output schema, the description must describe the return shape, and it does: status enum values, interpretation, product scoping, warnings and freshness markers. Nothing an agent needs to call or interpret this tool is missing.

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 the baseline is 3, but the description goes further by explaining `product` as a search restriction and by naming response-side concepts (`interpretation`, `warnings`, last-read timestamps) that have no output schema to carry them.

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

Purpose5/5

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

States a specific verb (answers a question) and resource (Sarnai's published documents for the Board, Verifier and Scores), and enumerates exactly which source documents are searched. An agent can distinguish this from siblings like find_agents or search_listings without opening any schema.

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?

Usage context is clear: ask plain-word questions about the three products' published docs, optionally narrowed via `product`. It doesn't explicitly name alternatives or state when NOT to use it, but the routing is unambiguous given the sibling set.

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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