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Clickup

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

A4.8/5.0
Behavior5/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context: parallel fan-out to multiple sources, fallback logic, soft-fail for patents, and return structure (changes[] grouped by source, total_changes, citation URIs). No contradictions with annotations.

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 a single dense paragraph but every sentence adds value. It could benefit from more structure (e.g., bullet points) but is not excessively long and front-loads the purpose. Slight deduction for lack of formatting.

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 the moderate complexity, no output schema, and excellent annotation coverage, the description is highly complete. It specifies input parameter meanings, sources, fallback, return structure, and sibling differentiation. No gaps.

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. The description adds meaning beyond schema by explaining the 'since' parameter accepts ISO dates or relative shorthand with examples, clarifies 'value' accepts ticker or CIK, and reinforces that 'type' is currently only 'company'. This extra context justifies a 4.

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 the tool returns a change feed for a company, including recent filings, news, and patents. It distinguishes from the sibling entity_profile tool by specifying that recent_changes is for dynamic changes over a window, while entity_profile 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?

The description provides explicit query examples ('What's new with X', 'latest on Y') and explicitly tells when to use entity_profile instead. It also explains fallback behavior (GDELT→GNews) and the soft-fail for patents.

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

A3.6/5.0
Disambiguation3/5

Many tools have distinct purposes, but there is overlap among query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research) and among prediction market tools. Detailed descriptions help differentiate, but the large number of tools increases chance of misselection.

Naming Consistency2/5

Naming is highly inconsistent, mixing snake_case and camelCase conventions. ClickUp tools use 'clickup_' prefix while Pipeworx tools have varied patterns (ask_, scan_, validate_, etc.). No unified convention across the set.

Tool Count2/5

35 tools is excessive for a server named 'Clickup', with only 6 ClickUp-specific tools. The remaining 29 are from Pipeworx, which is unrelated. The count is inappropriate for the server's stated purpose.

Completeness2/5

The ClickUp integration is incomplete, missing basic CRUD operations like update and delete tasks. The Pipeworx side is comprehensive but not relevant to the server's name. For a ClickUp server, coverage is poor.

Resources