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Themeparks

by io.github.pipeworx-io

Ask Pipeworx — Grounded

ask_pipeworx_grounded
Read-onlyIdempotent

Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 5,798 across 1517 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for question.
textNoAlias for question.
inputNoAlias for question.
queryNoAlias for question.
promptNoAlias for question.
questionYesYour question in natural language. Accepts query, q, prompt, text, input as aliases.

Schema Changelog

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

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description reveals refusal behavior, the exact refusal_reason enum, the guarantee that only tool results are used, and the return shape including evidence, confidence, and fetched_at. This is substantial behavioral disclosure that an agent needs to predict outcomes correctly.

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?

Every sentence earns its place: mode, routing behavior, return contract, refusal contract, use cases, and cost/alternative. The most important differentiator ('hallucination-resistant') is front-loaded, and the rest is dense but not padded.

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?

For a complex tool with no output schema, the description fully compensates by specifying success and refusal payloads, failure reasons, source behavior, and when to choose the sibling. Nothing an agent needs to decide between this and ask_pipeworx is missing.

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 schema fully documents the question parameter and its aliases. The description adds no new parameter-level detail beyond implying the natural-language question is the sole input. Baseline 3 is appropriate because the schema carries the semantic weight.

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 uses a specific verb ('answer') with a defined mode ('hallucination-resistant', 'grounded') and clearly distinguishes this tool from ask_pipeworx by stating it 'EXTRACTS the answer using ONLY what the tool result contains'. It also names the sibling routing and what makes this variant different, so an agent can select it without ambiguity.

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?

Explicitly states when to use the tool: 'whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts'. It also gives a direct alternative preference: 'prefer ask_pipeworx for casual lookups' and discloses the extra LLM call cost, making the trade-off concrete and actionable.

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

All Themeparks toolsInspect
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TDQS

A3.6/5.0
Disambiguation3/5

Most tools have distinct, well-documented purposes, but several overlap or are explicitly redundant: ask_pipeworx_beta currently behaves identically to ask_pipeworx, discover_tools and suggest_questions both serve as discovery entry points, and scan_competitor_ai_presence wraps ai_visibility_check. The thematic split between theme-park, data-lookup, prediction-market, and memory tools also forces agents to navigate unrelated clusters.

Naming Consistency3/5

Naming is a mix of verb_noun (list_destinations, get_wait_times, remember, resolve_entity), noun_phrase (entity_profile, recent_changes, bet_research), and brand-prefixed nouns (polymarket_edges, pipeworx_trending). Within families the patterns are consistent, but across the set the conventions are inconsistent and sometimes reverse the verb/noun order, making the surface harder to predict.

Tool Count2/5

35 tools is heavy, and the server is named Themeparks yet only 4 tools actually relate to theme parks. The remaining 31 tools span Pipeworx data retrieval, prediction markets, memory, subscriptions, and feedback, creating a bloated and misaligned scope. A tightly scoped theme-park server would need far fewer tools, and a general data research server would not be named Themeparks.

Completeness2/5

For the implied theme-park domain, the surface is thin: list destinations, get entity metadata, get schedule, and get wait times cover basic lookups but omit search, attraction details beyond waits, historical data, pricing, dining/show info, and park updates. The non-theme-park tools are extensive, but they do not complete the server's apparent stated purpose.

Resources