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Tcgdex

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

A4.9/5.0
Behavior5/5

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

Beyond annotations (readOnlyHint, openWorldHint, idempotentHint), the description adds detailed behavioral context: it pulls latest 10-K data from SEC EDGAR/XBRL for companies, handles off-calendar fiscal years, and for drugs pulls FAERS adverse-event counts. It also clarifies sorting and output format. 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.

Conciseness4/5

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

The description is longer than typical but every sentence adds value, with front-loaded examples and clear structure. Slight redundancy in listing query patterns could be trimmed, but it's justified by the tool's complexity.

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 no output schema, the description compensates by describing return format (paired data + citation URIs) and edge cases (off-calendar fiscal years). For a comparison tool with 2 parameters, it covers all necessary context for correct usage.

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?

Schema coverage is 100%, but the description adds significant meaning: it explains that type='company' retrieves specific financial metrics and type='drug' retrieves specific counts, and clarifies that values are tickers/CIKs or drug names. This greatly aids correct invocation.

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 specific examples. It distinguishes from sibling tools like entity_profile by explicitly recommending this tool over sequential single 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?

The description explicitly says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities' and provides concrete query patterns like 'compare X and Y', 'which is bigger', etc., making it clear when to use this tool.

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

All Tcgdex toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

The four card tools are distinct, but the majority of the server is a Pipeworx/prediction-market platform with heavily overlapping entry points: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and discover_tools all serve similar query/discovery purposes, and ask_pipeworx_beta is explicitly an identical twin of ask_pipeworx. The six Polymarket tools and the ai_visibility/scan_competitor pair also have fuzzy boundaries that would make tool selection error-prone.

Naming Consistency2/5

All names are snake_case, but the pattern is highly inconsistent: some are verb_noun (get_card, search_cards, resolve_entity), some are bare verbs (remember, forget), some are noun-first (polymarket_edges, entity_profile, bet_research), and some are adjective_noun (recent_alerts, recent_changes). The ask_pipeworx variants share a name but differ only by suffix, which is not a clear action-oriented pattern.

Tool Count2/5

35 tools is squarely in the 'too many' territory, and the bloat is worse because the server is named Tcgdex while only 4 of 35 tools actually relate to trading cards. The remaining 31 tools form a sprawling multi-domain platform that mixes data queries, prediction markets, memory, subscriptions, AI visibility checks, and one-off utilities like generate_llms_txt and scan_dependency.

Completeness4/5

For the TCGdex card surface, the read-only workflows are covered well: search_cards leads to get_card, and list_sets leads to get_set, with no obvious dead ends. For the broader Pipeworx functionality, the set includes discovery, query, grounding, entity resolution, memory, subscriptions, and feedback, so the main workflows are supported—though the overall scope is sprawling rather than focused.

Resources