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Packagephobia

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate non-destructive, read-only, idempotent behavior. The description adds significant context: fan-out to multiple sources, fallback mechanisms, return structure (changes[] grouped by source, total_changes, citation URIs), and soft-fail for USPTO.

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 moderately long but well-structured. It front-loads example queries and clearly separates sections. Every sentence adds value, though some minor redundancy exists (e.g., repeating the window concept). Still efficient.

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 no output schema, the description explains the return structure and behavior comprehensively. It covers all parameters, edge cases (relative dates, CIK vs ticker), and source fallbacks. Complete for a complex, multi-source tool.

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%, so baseline is 3. Description adds extra meaning: 'since' accepts ISO or relative shorthand with examples, 'value' can be ticker or CIK, 'type' only supports company. This goes 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 explicitly states the tool's purpose as a change feed for a company over a recent time window, with specific verb+resource (retrieve changes) and clear scope (multiple sources). It distinguishes from sibling 'entity_profile' which is for static profiles.

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?

Provides explicit when-to-use guidance, including the alternative 'entity_profile' for static profiles. Also describes fallback behavior between GDELT and GNews, and soft-fail for USPTO, helping the agent decide when to invoke this tool.

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.

Resources