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Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, lowering the bar. The description adds valuable behavioral context: return of top-N tools with full schemas and the 'no second schema lookup needed' guarantee, which are not covered by annotations.

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 a single, information-dense paragraph that front-loads the verb and resource. Every sentence adds value: what it does, when to use it, what it returns, and an explicit recommendation to call it first. No redundancy or 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?

For a discovery tool with no output schema, the description adequately explains return values (top-N tools with names, descriptions, schemas) and usage context. Combined with rich schema annotations, the agent has sufficient information to deploy the tool correctly.

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% with descriptions and examples for all parameters, so baseline is 3. The description adds a broad list of domains (SEC filings, financials, etc.) that helps formulate queries, which is extra value beyond the schema's two examples. Minor deduction because aliases and limit are already well-documented.

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 'Find tools by describing the data or task' and lists specific domains (SEC filings, FDA drugs, etc.), making it distinct from siblings. It also explains the return format, further clarifying its purpose.

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 says 'Use when you need to browse, search, look up, or discover what tools exist' and advises 'Call this FIRST when you have many tools available.' This gives clear when-to-use guidance and implies a workflow, though it does not name specific alternatives.

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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TDQS

A3.5/5.0
Disambiguation2/5

Multiple tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer research questions, and the Kitsu-specific tools are mixed with unrelated Polymarket, memory, and utility tools. Despite detailed descriptions, the boundaries between many tools are unclear.

Naming Consistency2/5

The server mixes single-word nouns (anime, manga, categories), verb_noun pairs (search_anime, top_anime), verb phrases (ask_pipeworx, generate_llms_txt), and domain-prefixed families (polymarket_*, pipeworx_*) with no consistent overall convention. While some sub-families are internally consistent, the set as a whole lacks a predictable pattern.

Tool Count2/5

38 tools is excessive for a server ostensibly about Kitsu anime/manga, with only 7 tools actually serving that domain. The rest are unrelated (Pipeworx research, Polymarket trading, memory, subscriptions), making the set bloated and unfocused for its stated purpose.

Completeness2/5

The Kitsu domain lacks common operations like filtered search, character/episode data, or user lists. Meanwhile, the Pipeworx/prediction-market tools form an arbitrary subset of their domains (e.g., no general Kalshi data, no SEC full-text search), so the overall surface is incomplete for any single purpose.