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Glama

Packagephobia

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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

The description adds detail beyond annotations: results include full schemas with curated examples, ready to call. Annotations already indicate read-only, idempotent, non-destructive. No contradictions.

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 well-structured and front-loaded with the purpose. It efficiently lists domains and output details without redundancy. Minor wordiness but overall effective.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers purpose, usage, and return structure well. However, it lacks details on error handling, behavior when no tools match, or result limit enforcement beyond schema's max 50. Adequate for the complexity.

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?

Parameter schema coverage is 100%, so baseline is 3. The description mentions query accepts aliases (task, q, description, search) but that is already in the schema. It adds no new semantic meaning beyond what the schema provides.

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 uses a specific verb 'find tools' and clearly states the resource as tools by describing task/data. It lists many example domains and distinguishes itself as a meta-tool for discovery, contrasting with sibling tools that are domain-specific.

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 advises 'Call this FIRST when you have many tools available and want to see the option set', providing clear usage context. It does not state when not to use, but the guidance is strong for a tool that is unique among siblings.

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
Disambiguation2/5

Several near-overlapping query tools exist: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same underlying catalog, and ask_pipeworx_beta is currently described as identical to ask_pipeworx. The Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker) also heavily overlap and rely on lengthy descriptions to keep them apart.

Naming Consistency3/5

The set is uniformly snake_case and generally readable, but conventions are mixed: verb_noun (resolve_entity, suggest_questions), noun_verb (bet_research, ai_visibility_check), noun_adj (pipeworx_trending, recent_changes), and bare verbs (size, forget, recall) all appear. Variant suffixes like ask_pipeworx_beta and ask_pipeworx_grounded add further unpredictability.

Tool Count2/5

32 tools exceeds the 'too many' threshold and spans unrelated domains: package size, general data research, prediction markets, memory, and subscription management. The set would feel more coherent at roughly half the count, with several query and Polymarket tools consolidated.

Completeness3/5

For the dominant data-research purpose, the surface is reasonably complete: querying, grounded verification, deep research, entity resolution, entity profiles, comparisons, claim validation, and discovery are all covered. However, the server's stated identity ('Packagephobia') is nearly absent—only `size` and `scan_dependency` address package sizing—so the namesake domain is thin while unrelated domains are overbuilt.

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