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Glama

Zendesk

by io.github.pipeworx-io

Compare Entities

compare_entities
Read-onlyIdempotent

"Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type: "company" or "drug".
valuesYesFor company: 2–5 tickers/CIKs (e.g., ["AAPL","MSFT"]). For drug: 2–5 names (e.g., ["ozempic","mounjaro"]).

Schema Changelog

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

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds rich behavioral context: results sorted by primary metric, data sources (SEC/FDA), handling of off-calendar fiscal years, and output format (paired data + URIs). This goes well 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.

Conciseness4/5

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

The description is relatively long but front-loaded with example queries and a clear recommendation. Each sentence adds value, though some minor redundancy (e.g., 'side-by-side' and 'comparison') could be trimmed. Overall well-structured.

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?

Given the tool's low complexity (2 params, no output schema), the description adequately covers inputs, outputs (sorted, paired data, URIs), data sources, and edge cases (off-calendar years). With annotations covering safety, it is sufficiently complete.

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%, but the description adds meaning: for 'type', it explains what data each enum value pulls; for 'values', it specifies input formats (tickers/CIKs for companies, drug names) and provides examples. This enhances understanding beyond the schema.

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 it performs side-by-side comparison of 2–5 companies or drugs in one call. It uses specific verbs like 'compare' and 'rank', and explicitly distinguishes from sequential single-pack lookups, which are sibling-adjacent actions.

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?

The description strongly recommends using this tool over sequential lookups when comparing entities, and provides example queries. However, it does not explicitly mention when not to use it (e.g., for more than 5 entities or non-entity comparisons), though the schema's maxItems imposes a limit.

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

B3.3/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially the Pipeworx query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, validate_claim) which all provide factual answers, making it unclear which to use. The set also mixes Zendesk tools with a large number of prediction market and data tools, creating confusion.

Naming Consistency2/5

Naming conventions are inconsistent: Zendesk tools use 'zd_' prefix, Pipeworx tools use various prefixes like 'ask_', 'bet_', 'compare_', etc., and some are named with full words. There is no uniform pattern across the set.

Tool Count2/5

35 tools is high for a server named 'Zendesk', especially since only 5 are Zendesk-specific. The majority are unrelated to Zendesk, indicating the tool count is inappropriate for the implied purpose.

Completeness1/5

For a Zendesk server, the tool set is severely incomplete, offering only basic CRUD operations (get, list, search for tickets and users). Missing essential Zendesk features like ticket creation, update, delete, or macros, while containing many irrelevant tools from other domains.

Resources