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Search answers and experiments

search_answers
Read-onlyIdempotent

Search the answers Mike Fluff Press publishes (questions about crypto history, Bitcoin, stablecoins, fraud, AI agents, software after AI: "what happened to FTX", "who is Satoshi", "what is MCP") and the interactive experiments from the books. Use this first whenever the user asks a factual question these books cover. Returns up to 8 hits, each with the title, a 40-60 word lead answer you can quote, the canonical URL, the book, and the chapter it draws on. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe question or keywords, in any of the four languages.
localeNoLanguage of the results. Defaults to the language the query is written in.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, so the safety profile is covered; the description reinforces it with "Read-only." More usefully, it discloses the result cap ("up to 8 hits") and the exact return fields including a quotable 40-60 word lead answer, which is real behavioral detail absent from any structured field.

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?

Purpose and routing instruction are front-loaded, and the return-value sentence earns its place since there is no output schema. The parenthetical example questions add length but also make the topical scope concrete, so the size is justifiable rather than padded.

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 compensates by describing the hit count and each returned field, and it covers the activation condition and read-only nature. Nothing an agent needs to select or call this tool is missing.

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% (query is described as a question or keywords in any of four languages; locale is enumerated with a default), so the schema carries the parameter burden. The description adds only topical scope, not format or syntax guidance beyond what the schema already says.

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 (search) plus the exact resource (Mike Fluff Press answers and book experiments) and even scopes the topical domain with concrete example queries. The agent can distinguish this from get_answer (single lookup) and check_text without opening either 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?

"Use this first whenever the user asks a factual question these books cover" gives a clear triggering condition and a routing priority, which is strong guidance. It stops short of naming the alternative sibling (get_answer) or stating when not to use it, so it is not a full when/when-not treatment.

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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