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Geoboundaries

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 hints, the description discloses meaningful behavioral traits: it makes an extra LLM call, extracts answers only from tool result content, returns verbatim evidence, and refuses with specific enumerated reasons when the data does not directly answer. This gives agents a clear model of failure behavior.

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 dense but every sentence adds value: it front-loads the core differentiator, then covers return structure, refusal reasons, usage guidance, and cost trade-off. No filler or redundant restating of schema fields.

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 tool with no output schema, the description compensates thoroughly by specifying the success response shape, the refusal response shape, the refusal reason enums, and the exact condition under which refusal occurs. Combined with 100% parameter schema coverage, the agent has enough to select and invoke the tool 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 coverage is 100% and documents question plus five aliases with descriptions. The tool description adds no additional parameter semantics beyond 'fills arguments' and natural-language question usage, so the schema already carries the burden. Baseline 3 is appropriate.

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 states a specific purpose: a hallucination-resistant grounded answer mode that extracts answers only from tool results. It clearly distinguishes itself from sibling ask_pipeworx by highlighting the grounding behavior, structured evidence output, and explicit refusal mechanism.

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 explicitly says when to use this tool: when answers will be quoted, cited, or acted on and facts must not be invented, with concrete examples like financial verdicts, legal claims, and medical lookups. It also names the alternative, ask_pipeworx, and advises preferring it for casual lookups due to the extra LLM call cost.

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

A3.8/5.0
Disambiguation2/5

Many tools have overlapping or unclear purposes, e.g., multiple entity research tools (entity_profile, recent_changes, compare_entities, validate_claim) and several betting tools (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_kalshi_spread). The memory tools (remember, recall, forget) and generic lookup tools (ask_pipeworx, discover_tools) further blur boundaries, making it hard for an agent to consistently select the right tool.

Naming Consistency2/5

Tool names follow no consistent pattern: some use snake_case verbs (forget, recall, remember), others are noun phrases (entity_profile, recent_changes), and many have mixed conventions (ai_visibility_check, ask_pipeworx, bet_research). There is no clear verb_noun structure, and the naming style varies widely across the set.

Tool Count3/5

At 22 tools, the count is within a reasonable range, but the server's stated purpose ('Geoboundaries') is severely mismatched with the actual tool set, which covers data retrieval, betting, memory, and more. The number is not excessive for the breadth of functionality, but it feels bloated for a server that should be focused on geographic boundaries.

Completeness1/5

The server is named 'Geoboundaries' but only provides two boundary-related tools (get_boundaries, get_geometry). The remaining 20 tools are unrelated, covering general data access, betting arbitrage, and memory operations. This leaves massive gaps for the implied domain (no tools for boundary editing, search by location, or other geographic operations) while over-supplying tools for unrelated tasks.

Resources