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Glama

Unicode

by io.github.pipeworx-io

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

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false. The description adds detail: 'Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly.' This enriches the agent's understanding beyond the 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?

Two paragraphs, no wasted words. The opening sentence front-loads the purpose, followed by a list of domains and a clear instruction to use it first. Every sentence serves a purpose.

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?

Given the tool's moderate complexity (6 params, no output schema), the description covers purpose, usage, and return format. It omits the default/max limit values, but these are in the schema, so the description is largely complete.

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% with detailed parameter descriptions and examples. The description mentions alias acceptance ('Accepts task, q, description, search as aliases') but adds minimal meaning beyond the schema, meeting the baseline for high coverage.

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's purpose: 'Find tools by describing the data or task.' It lists specific domains (SEC filings, FDA drugs, etc.) and distinguishes it from siblings by instructing 'Call this FIRST when you have many tools available,' which sets it apart from other tools like search_within or deep_research.

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 'Use when you need to browse, search, look up, or discover what tools exist for:' and instructs 'Call this FIRST.' This gives clear usage context, though it does not explicitly name alternatives or when not to use it.

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

A3.8/5.0
Disambiguation3/5

Several tools overlap significantly: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded serve nearly the same routing purpose, with the beta variant currently identical to the stable one, and deep_research also overlaps for broad research. However, most other tools have clearly distinct functions, and descriptions provide usage guidance, so ambiguity is moderate.

Naming Consistency3/5

Most names are snake_case and readable, but patterns vary between verb_noun (compare_entities, resolve_entity), noun phrases (entity_profile, polymarket_edges), and bare verbs (remember, subscribe). The pipeworx_ and polymarket_ prefixes are used inconsistently across the set, and the server name 'Unicode' does not align with the tool names.

Tool Count2/5

At 34 tools, the server is overloaded for a focused purpose, especially since only three tools relate to Unicode despite the server name. Many Polymarket and Pipeworx tools could be consolidated, and the count exceeds the well-scoped range of 3-15 tools, making the set feel bloated and unfocused.

Completeness2/5

The server name claims to be about Unicode, but only char_info, escape_string, and unescape_string cover that domain, missing common operations like normalization, case conversion, and encoding validation. For the broader data-access domain the surface is fairly complete, yet there is no tool to fetch a specific pipeworx:// citation URI, leaving cited records unfetchable within the tool set—an obvious gap relative to the stated capabilities.

Resources