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Jsonplaceholder

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

A4.5/5.0
Behavior5/5

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

The description discloses specific runtime behaviors beyond annotations, including GDELT-to-GNews fallback on rate limit/5xx, soft-failure of USPTO due to PatentsView sunset, and the return structure with citations. This complements the readOnly/idempotent hints with actionable details.

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 information-dense and well-structured, but the opening list of six example paraphrases is somewhat redundant. However, each section (purpose, parameters, fallback, return, alternative) earns its place, and the critical details are front-loaded.

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?

For a tool with no output schema, the description covers return shape (changes[], total_changes, citation URIs), source specifics, and parameter semantics. It lacks minor edge-case details (e.g., behavior for invalid tickers, coverage limits) but is sufficiently complete for an agent to select and invoke correctly.

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%, and the description largely repeats parameter details: `since` formats, `value` as ticker/CIK, and `type` as 'company'. It does not introduce additional meaning beyond what the schema already specifies, so the baseline 3 applies.

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 identifies the tool as a change feed for a company, supporting queries like 'What's new with X' and listing specific data sources (SEC EDGAR, GDELT/GNews, USPTO). It explicitly differentiates from entity_profile by contrasting dynamic changes with 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 usage context via natural-language examples ('What's new with X') and a direct alternative: 'Use entity_profile instead when you want the static profile...'. Also describes the parallel fan-out behavior, clarifying when to rely on this tool for multi-source updates.

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

A3.7/5.0
Disambiguation2/5

Multiple tools overlap heavily: ask_pipeworx_beta is explicitly identical to ask_pipeworx, and ask_pipeworx, ask_pipeworx_grounded, deep_research, and validate_claim all serve natural-language question answering. The JSONPlaceholder get_* tools are distinct but introduce an unrelated domain, making tool selection ambiguous in practice.

Naming Consistency3/5

All names use lowercase snake_case, which is a consistent style, but there's no uniform verb_noun pattern. Tools mix action-first names (get_posts, remember, resolve_entity) with noun-oriented names (entity_profile, deep_research, pipeworx_trending). The naming is readable but not highly predictable.

Tool Count2/5

35 tools is far beyond the typical well-scoped range of 3-15. The set includes a full suite of Pipeworx/Polymarket tools plus a separate JSONPlaceholder demo namespace, making the server feel bloated and unfocused. Many meta-tools (discover_tools, suggest_questions, pipeworx_trending) could be consolidated.

Completeness2/5

The server's name and the get_posts/get_post/get_comments/get_users tools suggest a JSONPlaceholder fake API, but CRUD operations are missing: there's no create, update, or delete for posts, comments, or users, and no todos, albums, or photos. The unrelated Pipeworx/Polymarket tools don't address this core domain gap.

Resources