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Glama

Chargebee

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

A4.8/5.0
Behavior5/5

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

Beyond annotations (readOnly, openWorld, idempotent, non-destructive), description reveals key behaviors: pulls latest 10-K data with proper fiscal year handling for companies, and FAERS/FDA/trial counts for drugs. Also mentions sorted results and citation URIs, providing rich behavioral context.

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?

Description is information-dense but front-loaded with trigger phrases. Every sentence adds value, but slight verbosity could be trimmed. Still well-structured and efficient.

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 complexity (two entity types, multiple data sources, sorting, citations) and no output schema, the description fully covers what the tool does, how it works, and what it returns. No gaps for an agent to select and invoke correctly.

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. Description adds value by explaining that 'values' should be tickers/CIKs for companies and drug names for drugs, and specifies min/max constraints beyond 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?

Description clearly defines the tool as performing side-by-side comparisons of 2-5 companies or drugs, using trigger phrases like 'compare X and Y' and 'which is bigger'. It explicitly distinguishes itself from sequential single-pack lookups and sibling tools like entity_profile.

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?

Provides explicit guidance on when to use: when comparing, ranking, or head-to-head queries. States 'ALWAYS PREFER over sequential single-pack lookups' and clarifies the behavior for each entity type (company vs drug), including result sorting by primary metric.

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

All Chargebee toolsInspect
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TDQS

B3.3/5.0
Disambiguation1/5

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all answer questions or discover data via the same routing engine, with ask_pipeworx_beta explicitly stated to be identical to ask_pipeworx. Polymarket tools (arbitrage, edges, edge_tracker, fill_risk) also blur together, and ai_visibility_check overlaps with scan_competitor_ai_presence.

Naming Consistency2/5

Some clusters are consistent (chargebee_list_*/chargebee_get_*, polymarket_*, pipeworx_*), but the set mixes snake_case with varying verb styles and many unprefixed tools (remember, recall, forget, subscribe, unsubscribe, validate_claim). The 5 Chargebee tools use a clean prefix while the other 31 tools follow several different conventions, making the overall pattern unpredictable.

Tool Count2/5

36 tools is excessively heavy for a server named Chargebee, especially since only 5 tools actually relate to Chargebee. The remaining 31 tools form a broad Pipeworx/prediction-market/utility toolkit that has little connection to the server's apparent billing purpose, making the count feel bloated and unfocused.

Completeness1/5

The Chargebee-specific surface is severely incomplete: it only supports reading customers, subscriptions, and invoices, with no create, update, delete, payment, dunning, coupon, or plan-management operations. The rest of the tools belong to unrelated domains, so the set as a whole has no coherent lifecycle coverage and would leave agents unable to perform even basic Chargebee management tasks.

Resources