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Open Contracting

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

A4.4/5.0
Behavior4/5

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

Annotations already indicate safe read-only operation. The description adds valuable behavioral details: what data is pulled per type, handling of off-calendar fiscal years, sorted results, 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.

Conciseness4/5

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

The description is longer but every sentence adds value. It starts with examples, states core function, then adds details. Could be slightly trimmed but overall efficient for the complexity.

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?

No output schema, but description mentions return includes paired data and citation URIs. It covers key aspects like metric sorting and data sources. Additional specificity on output formatting would improve completeness.

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 still enriches understanding by explaining how each type affects data retrieval (financials vs. safety counts) and how the values parameter should be formatted (tickers/CIKs for company, names for drug). This goes well 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 entities (companies or drugs) in one parallel call. It provides example queries and distinguishes itself from sequential single-entity lookups, making the purpose unmistakable.

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?

Explicitly advises preference over sequential single-pack lookups when comparing entities. While it doesn't name alternative tools, it contrasts with the sibling 'entity_profile' (single entity) and implies not to use for single queries.

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

All Open Contracting toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Several tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve query/discovery purposes; polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, and bet_research all target prediction-market opportunity detection. ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, making the distinction essentially invisible without deep description parsing.

Naming Consistency3/5

Names mix domain prefixes (oc_*, polymarket_*, pipeworx_*), action verbs (validate_claim, resolve_entity, generate_llms_txt), and plain nouns (entity_profile, recent_alerts, recent_changes). Most are readable snake_case, but there is no uniform verb_noun or domain-first convention, so the set feels stylistically fragmented rather than patterned.

Tool Count2/5

35 tools is a heavy surface for a server ostensibly named 'Open Contracting' — only 4 of the 35 tools actually relate to open contracting data. The rest sprawl across general data lookup, prediction markets, memory, subscriptions, npm scanning, and AI visibility, making the tool count feel bloated and unfocused relative to the stated purpose.

Completeness2/5

For the open-contracting domain implied by the server name, the surface is incomplete: there is coverage metadata, search, recent releases, and process history, but no direct retrieval of a single release by ID and no broader OCDS exploration tools. As a general data/Pipeworx toolkit the coverage is wide, but the severe mismatch between the server name and the actual tool set creates a significant gap between expectation and capability.

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