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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

A4.1/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that the tool returns top-N relevant tools with schemas and examples ready to call, which adds useful behavioral context beyond annotations.

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?

The description is front-loaded with purpose and lists many domains, which is helpful. While slightly long, every sentence contributes value. Could be trimmed slightly but is well-structured.

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?

Despite having no output schema, the description explains the return format (top-N tools with names, descriptions, full schemas, examples). Parameters are fully covered, and the tool's role as a discovery tool is well-specified.

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 all 6 parameters are documented in the schema. The description mentions aliases (task, q, description, search) but does not add significant new meaning beyond the schema.

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 the tool discovers tools by describing data or task, lists many example domains (SEC filings, FDA drugs, etc.), and distinguishes itself from sibling tools by advising 'Call this FIRST when you have many tools available and want to see the option set.'

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?

Explicitly states when to use: 'when you need to browse, search, look up, or discover what tools exist' and 'Call this FIRST...'. Implies not to use when you already know the tool, but does not list specific alternative tools.

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

B3.4/5.0
Disambiguation2/5

The vast majority of tools are unrelated to GitLab and cover overlapping domains (multiple ask_pipeworx variants, several Polymarket tools, memory tools). Only three GitLab-specific tools exist, and they are distinct from each other, but overall the set is highly heterogeneous and ambiguous.

Naming Consistency2/5

Tool names use a mix of conventions: some are snake_case (ask_pipeworx, search_issues), some are compound nouns (get_project, list_subscriptions), and a few are single words (forget, recall). There is no consistent pattern, making it harder to predict tool names.

Tool Count1/5

Despite the server name 'Gitlab Public', only 3 out of 34 tools are related to GitLab. The remaining 31 tools are a collection of unrelated services (Pipeworx data retrieval, Polymarket betting, memory, AI visibility). This is a severe mismatch between the server's stated purpose and its tool composition.

Completeness1/5

For a GitLab public server, essential tools like project creation, deletion, user management, and merge request handling are completely missing. The Pipeworx tools, while numerous, lack a clear cohesive scope and overlap significantly with each other.