Ada Diamonds

Search Ada Diamonds guides

search_knowledge_base

Read-only

Search Ada Diamonds' published guides on lab grown diamonds — the 4Cs, CVD vs HPHT growth, shape guides, certification, and buying advice. Returns article summaries and markdown URLs. Use read_article to get an article's full text.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of results to return, 1 to 25 (default 8)
`query`	Yes	Topic to search for, matched against article titles, summaries, and slugs
`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."
`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.
`conversation_id`	No	Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.

Output Schema

TableJSON Schema

Name	Required	Description
`kind`	Yes	Always "articles"
`items`	Yes	Matching articles
`query`	Yes	The search terms that were used
`total`	Yes	How many articles are in `items`
`browseUrl`	Yes	Web page listing every guide

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedSep 18, 2026

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 / conversation_id

Added value: +{
+  "description": "Echo the conversation_id from the server's previous response. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it.",
+  "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 / required

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

First observedSep 1, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe, non-mutating search. The description adds that it returns article summaries and markdown URLs, which is useful behavioral context beyond the annotations. However, it doesn't disclose pagination behavior, result ordering, or what happens with no results. With annotations covering the safety profile, a 3 is appropriate.

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 with zero waste. The first sentence front-loads the tool's purpose and scope, and the second provides a clear pointer to the sibling tool for the next step. Every word 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 states what it searches, what it returns (summaries and markdown URLs), and how to get full text. The output schema exists, so return values don't need explanation. Minor gaps like result ordering and pagination are not critical for an agent to invoke this tool correctly. The only slight gap is not explicitly distinguishing from search_diamonds, but the topic scope makes it clear.

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 the schema already documents all 5 parameters thoroughly. The description adds context about what 'query' matches against (article titles, summaries, and slugs) and that results include summaries and URLs, which slightly enriches the schema. But the description doesn't add meaning beyond what the schema provides for the other parameters (context, llm_model, conversation_id, limit). Baseline 3 is correct when schema does the heavy lifting.

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?

The description states a specific verb ('Search'), a specific resource ('Ada Diamonds' published guides on lab grown diamonds'), and enumerates the covered topics (4Cs, CVD vs HPHT, shape guides, certification, buying advice). It also distinguishes itself from read_article by noting it returns summaries and URLs while read_article provides full text. This clearly differentiates it from siblings like search_diamonds and search_engagement_rings.

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?

The description explicitly says to use read_article to get an article's full text, which provides a clear alternative for a follow-up action. It implies this tool is for finding/summarizing articles rather than reading them fully. However, it doesn't explicitly state when NOT to use this tool versus other search siblings (e.g., search_diamonds for product searches), though the topic scope makes this reasonably clear.

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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