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Search FLOX documentation to find how-to guides, reference pages, tutorials, and error codes. Use it to answer questions about FLOX behavior, configuration, or APIs by grounding responses in actual docs.

Instructions

Top-k full-text search over the FLOX documentation (how-to guides, reference pages, tutorials, error codes, bindings overviews, explanations). Use this to ground answers about FLOX behavior, configuration, or APIs in the actual docs instead of relying on training data — call it whenever the user asks 'how do I X' / 'what does Y do' / 'where is Z documented'. The index is built from a strict allowlist; private tracker / strategy / author files are NEVER indexed.

Query syntax: plain word lists are AND-matched (every token must appear). Wrap a phrase in double quotes for exact match: "walk forward". FTS5 operators (OR, NEAR, *, parens) pass through.

Canonical workflow queries (run these instead of guessing the canonical path from training data): • User wants to record market data → docs_search('record tape'). Covers live capture and the ccxt.fetch_ohlcv historical-backfill pattern. • User asks 'how should I structure a flox project' → docs_search('project layout'). • User mentions an exchange / live data → docs_search('ccxt'). • User wants to backtest a strategy on a recorded tape → docs_search('backtest'). • User mentions strategy traces, signals, or .floxrundocs_search('floxrun').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesFree-text query. Plain word lists are AND-matched. Wrap a phrase in double quotes for exact match.
kNoNumber of results to return (1..25). Default 5.
Behavior4/5

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

With no annotations provided, the description carries full burden. It explains query syntax (AND matching, phrase, operators), indexing scope (strict allowlist, private files never indexed), and gives canonical queries. However, it does not mention whether the docs are from a fixed snapshot or live, or any rate limits.

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?

The description is well-structured: it starts with a concise purpose statement, then details query syntax, and ends with canonical workflow queries. Every sentence adds necessary information, and there is no filler.

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?

Given that the tool has only two parameters and no output schema, the description is complete. It covers what the tool searches, how to form queries, when to use it, and common use-case examples. No significant gaps.

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% as both 'query' and 'k' are described with types and default. The description adds value by elaborating on query syntax (e.g., 'Wrap a phrase in double quotes for exact match') and providing example queries, which goes beyond the schema's basic descriptions.

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 clearly states it performs 'Top-k full-text search over the FLOX documentation' and lists specific types of documents it covers. It distinguishes itself from sibling tools by focusing on documentation grounding rather than other actions like order placement or strategy validation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly tells the agent to use this tool 'whenever the user asks 'how do I X' / 'what does Y do' / 'where is Z documented'' and provides canonical workflow queries mapping common user intents to specific search terms. It also contrasts with relying on training data.

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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