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Packagist

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").

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already indicate read-only, open-world, and idempotent behaviors. The description adds significant context: fan-out to multiple sources, fallback from GDELT to GNews, PatentsView sunset soft-fail, and the output structure. 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 with query examples first, then details on data sources and parameters. It is relatively long but every sentence adds value. Minor reduction could be made, but effective overall.

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?

Despite no output schema, the description explains the return format (changes grouped by source, total_changes, citation URIs). All three parameters have clear descriptions and examples. The tool's scope and limitations are fully covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds valuable usage examples: 'since' accepts ISO dates or relative shorthand (e.g., '30d'), 'value' can be ticker or CIK, and 'type' is limited to 'company'. It also suggests typical monitoring windows like '30d' or '1m'.

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 it provides a change feed for a company, combining SEC filings, news, and patents in one call. It gives specific query examples and distinguishes from the sibling tool '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?

Explicit use cases are provided ('What's new with X', 'latest on Y', etc.), along with when to use an alternative ('Use entity_profile instead when you want the static profile'). It also details fallback behavior and soft-failures.

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

B3.3/5.0
Disambiguation2/5

Many tools have overlapping purposes: ask_pipeworx_beta is a literal duplicate of ask_pipeworx, and ai_visibility_check/scans overlap with each other while the many prediction-market and edge tools cover similar ground. The verbose descriptions help somewhat, but an agent would frequently struggle to pick the right tool.

Naming Consistency2/5

Naming is inconsistent: some tools use verb_noun (get_package, list_versions), others noun_verb (ai_visibility_check, bet_research), and several are brand-specific (pipeworx_feedback, pipeworx_trending) with no uniform verb style. The mixed patterns make it hard to predict tool names.

Tool Count1/5

35 tools is far too many for a server named Packagist: only 4-5 tools relate to the PHP/Composer registry while the vast majority concern Pipeworx data lookups, Polymarket analysis, and memory utilities. The scope is severely mismatched with the server's name and apparent purpose.

Completeness2/5

For a Packagist registry server, the core read operations (search, get, list versions, stats) are present, but the server is cluttered with unrelated functionality and offers no package management actions. The tool set is not complete for any single, coherent domain, making it feel like two different servers merged into one.

Resources