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Bundlephobia

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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable context about behavior: it returns 'top-N most relevant tools with names, descriptions, and full input schemas (with curated examples)' and that results are 'ready to call directly, no second schema lookup needed.' This goes beyond the annotations to explain what the user gets and how to use the output.

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 concise but information-dense. It packs the action, use case, domain list, return behavior, and usage advice into three sentences with no redundancy. The structure front-loads the verb and resource, making it easy to scan.

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 its simplicity (one required parameter, no output schema), the description fully covers what the tool does, when to use it, what it returns, and how the output is ready for direct use. It is complete for a discovery tool and leaves no major gaps in understanding.

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 parameters (query, aliases, limit) are already well documented. The description does not add additional parameter semantics beyond what the schema provides, but it includes examples that reinforce the query format. With high schema coverage, a baseline of 3 is appropriate.

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 enumerates the domains it covers, making the purpose specific and actionable. It differentiates from sibling tools by emphasizing discovery and 'Call this FIRST' for exploring available tools, which is distinct from direct-answer or research tools.

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 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 and want to see the option set (not just one answer).' This gives clear when-to-use guidance, though it stops short of naming specific alternative tools or explicit exclusions, which would push it to a 5.

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

A3.9/5.0
Disambiguation2/5

There is substantial overlap among tools in the Pipeworx group: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route natural-language queries to the same 5,578 tools and sources, with only subtle differences in mode (beta vs stable, grounded vs standard, single vs multi-part). Similarly, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, and polymarket_fill_risk are heavily intertwined, making differentiation difficult. Tools like similar, size, history, and scan_dependency from the bundlephobia side are distinct, but the Pipeworx family muddies the set.

Naming Consistency3/5

The bundlephobia tools follow a consistent noun pattern (size, similar, history), and the Pipeworx meta-tools use snake_case verbs (ask_pipeworx, resolve_entity, compare_entities, validate_claim). However, the naming is inconsistent across the two families—bundlephobia's simple nouns (size, similar, history) clash with the verbose descriptive verbs—and naming like ai_visibility_check, scan_competitor_ai_presence, and generate_llms_txt break from the Pipeworx pattern. The set mixes short names, camelCase-ish compounds, and snake_case, so no single consistent convention holds.

Tool Count2/5

35 tools is too many for a server that ostensibly serves two domains (bundle-size analysis and Pipeworx data research). The bundle-size analysis needs only a handful (size, history, similar, recent_searches, scan_dependency), yet there are over 30 tools dominated by a sprawling meta-research layer including multiple ask_pipeworx variants, several polymarket tools, plus meta-cognitive tools (remember, recall, forget, discover_tools) that are not core to either domain. This bloats the surface and makes call routing difficult.

Completeness4/5

Each functional domain is fairly complete: bundlephobia covers size measurement, history, alternatives, search, and dependency vetting; the Pipeworx side covers lookup, research, entity resolution, comparison, verification, subscriptions, and feedback. However, there are gaps—e.g., no tool for directly reading an npm package's README or license beyond scan_dependency's summary, and no explicit tools for some administrative actions like account management or subscription editing beyond create/cancel/list. The completeness is strong for what's advertised but not exhaustive.

Resources