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Glama

Vimeo

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. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already indicate safe, read-only, idempotent behavior. The description adds rich behavioral context: data sources (SEC EDGAR/XBRL for companies, FAERS for drugs), fiscal year handling, sorting by primary metric, and citation URIs. No contradiction with 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?

Description is efficiently front-loaded with example triggers. Every sentence adds distinct value without redundancy. Well-structured and immediately informative.

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 the tool's simplicity (2 params, no output schema), the description fully covers input semantics, data sources, behavior, and output format (paired data + URIs). No gaps remain for effective agent use.

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 already describes both parameters with enums and ranges (100% coverage). Description adds value by specifying expected formats (tickers/CIKs for company, names for drug) and clarifying the behavior of the 'type' parameter.

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 the tool performs side-by-side comparison of 2-5 companies or drugs, with natural language examples. It specifies what data each type returns and differentiates from sequential single-pack lookups.

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 instructs to prefer this over sequential lookups when comparing entities. Provides clear criteria for choosing 'company' vs 'drug' and what data each provides.

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

B3.1/5.0
Disambiguation2/5

Several tools have overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-duplicates, and the polymarket_* family has six tools with blurred boundaries. The Vimeo tools are distinct, but the massive unrelated Pipeworx set creates ambiguity about which tool is appropriate for a given task.

Naming Consistency2/5

Tool names mix conventions: Vimeo tools use bare nouns (video, channel, user), while Pipeworx tools use verb_noun (resolve_entity, validate_claim) or noun_verb (ai_visibility_check). Some names like ask_pipeworx and pipeworx_feedback do not follow a consistent verb-first pattern.

Tool Count2/5

40 tools is far too many for a Vimeo server; only 9 tools are Vimeo-related, and the remaining 31 are an unrelated Pipeworx data toolkit. This inflates the surface area and makes the set unwieldy.

Completeness2/5

The Vimeo surface covers read operations (search, get, list) but lacks any write operations like upload, update, or delete videos. It also misses common Vimeo features like comments, likes, or portfolio management, so common tasks would hit dead ends.

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