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Tax Regulations

by io.github.pipeworx-io

Pipeworx Trending

pipeworx_trending
Read-onlyIdempotent

What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNo24h (default) | 7d | 30d. Shorter windows surface what's hot right now; longer windows show steady-state demand.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover safety (read-only, idempotent). The description adds valuable behavioral context: data source (CF analytics-engine), no PII, result structure (pack, tool, count), and caching behavior (5min-1h depending on window). This goes beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise yet comprehensive, with a front-loaded main statement. The 'Useful for' list is structured and every sentence contributes unique information. No filler or redundancy.

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?

The tool is simple (one optional parameter, read-only) and the description covers what it returns, why it matters, how it's derived, privacy implications, and caching. With no output schema, this level of detail is sufficient for an agent to invoke it 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%, so the parameter is already fully documented. The description does not add new semantic details about the 'window' parameter beyond the schema; it simply reuses the same values and adds a caching note, which does not enhance parameter understanding.

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 what the tool does: returns top tools, top packs, and total call volume over a recent window. It distinguishes from siblings like discover_tools by emphasizing it shows what other AI agents are calling on Pipeworx, not a general discovery mechanism.

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?

It provides three explicit use cases: discovering hot data sources, confirming canonical tool choice, and checking alignment with agent demand. It doesn't name alternatives or say when not to use, but the context is clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Tax Regulations toolsInspect
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TDQS

A3.5/5.0
Disambiguation2/5

Many tools overlap in purpose: ask_pipeworx and ask_pipeworx_beta are identical, while ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve as query/entry-point tools. The two tax-specific tools are distinct, but the sheer number of generic data-access tools makes it difficult for an agent to select the right one.

Naming Consistency2/5

Naming is a mix of snake_case (ask_pipeworx, tax_search), camelCase (ask_pipeworx_beta, compare_entities, discover_tools), and inconsistent verb styles (resolve_entity vs entity_profile vs scan_competitor_ai_presence). No clear pattern is discernible.

Tool Count1/5

The server is named 'Tax Regulations' but only 2 of 33 tools are tax-related. The other 31 tools are unrelated Pipeworx data-access, memory, subscription, and Polymarket tools, making the count wildly excessive and mismatched with the apparent purpose.

Completeness3/5

For the tax regulation domain, tax_search and tax_regulation cover keyword discovery and full-text retrieval, which is a functional core. However, the set lacks any other tax-specific operations (e.g., updates, comparisons, planning), and the majority of the tool surface is irrelevant to the stated server purpose, leaving notable gaps for an agent expecting a coherent tax toolset.

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