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Riot Games

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"]).

TDQS

A5/5.0
Behavior5/5

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

The description adds significant behavioral context beyond the annotations: for companies, it pulls specific financial metrics from SEC EDGAR/XBRL and handles off-calendar fiscal years; for drugs, it pulls FAERS, FDA, and trial data. It also notes results are sorted by primary metric and include pipeworx 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?

The description is concise yet comprehensive, with front-loaded examples and imperative instructions. Every sentence serves a purpose—no fluff. It structures information logically: examples, usage preference, type-specific details, and output format.

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?

Despite lacking an output schema, the description covers return data (paired data, sorted, with citation URIs) and input/behavior adequately. For a simple 2-parameter tool, it provides complete context for selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema coverage, the description adds valuable meaning: it explains that 'type' determines data source (SEC vs FAERS) and 'values' format (tickers/CIKs vs drug names). It provides concrete examples (AAPL, MSFT; ozempic, mounjaro), enhancing schema details.

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 comparisons of 2–5 companies or drugs in one parallel call, with specific query examples ('compare X and Y', 'which is larger'). It explicitly distinguishes itself from sequential single-pack lookups, establishing a unique purpose.

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 includes an explicit directive: 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' It specifies when to use the tool (comparison queries) and provides context on data sources per entity type, helping the agent decide between this and sibling tools.

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

All Riot Games toolsInspect
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TDQS

B3.1/5.0
Disambiguation2/5

Several tools have overlapping purposes: champion_mastery and summoner_top_mastery both return mastery data, and the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) plus deep_research all handle question-answering. The inclusion of an entire unrelated Pipeworx research suite under a Riot Games server creates cross-domain ambiguity, making it difficult to know which tool to select.

Naming Consistency3/5

Most tools use snake_case, but the pattern varies: resource_by_key (account_by_puuid), verb_noun (generate_llms_txt, compare_entities), bare verbs (forget, recall, remember), and standalone nouns (match, status). Pipeworx and polymarket tools share consistent prefixes, but the Riot tools and meta-tools break the pattern, resulting in a mixed but still readable convention.

Tool Count2/5

42 tools is far above the typical 3-15 for a focused server. Only 10 are Riot Games-specific; the remaining 28 are unrelated Pipeworx, data-research, Polymarket, and memory tools. The excessive count dilutes the server's purpose and makes it feel bloated.

Completeness3/5

The Riot Games domain is covered reasonably well with accounts, summoners, mastery, matches, and rankings, but misses common endpoints like champion static data and live match info. The extensive non-Riot tools do not fill these gaps and instead add an unrelated, separately complete surface that distracts from the server's apparent purpose.

Resources