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Glama

Mempool Space

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

A4.5/5.0
Behavior4/5

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

Annotations (readOnlyHint, openWorldHint, etc.) are complemented by description that covers fiscal year handling, sorting by primary metric, and return format with URIs. No contradictions; adds useful behavior beyond 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?

Description is comprehensive but front-loaded with trigger phrases. Every sentence adds value, though the fiscal year handling detail could be a separate note. Minimal waste.

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 complexity (two entity types, multiple data sources, no output schema), the description covers inputs, behavior, sorting, and return structure. It replaces 8-15 sequential lookups, making it complete for an AI agent.

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 has 100% coverage; description adds meaning by explaining what data each type pulls (SEC 10-K data for companies, FAERS for drugs) and providing examples ('AAPL, MSFT'), significantly enhancing 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 the tool compares 2-5 companies or drugs in one call, providing side-by-side data. It lists trigger phrases and explains the difference between entity types, distinguishing it from sequential sibling tools.

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 states 'ALWAYS PREFER over sequential single-pack lookups' and gives example queries. Does not list when not to use but provides sufficient context for appropriate usage.

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

All Mempool Space toolsInspect
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TDQS

B3.1/5.0
Disambiguation2/5

The set mixes two unrelated domains — Bitcoin mempool explorer tools and the much larger Pipeworx data-query platform — and within the Pipeworx half several tools route to the same 5,743-tool catalog (ask_pipeworx, deep_research, discover_tools, suggest_questions). ask_pipeworx_beta is currently an exact behavioral duplicate of ask_pipeworx, and the polymarket_* family has fuzzy boundaries (arbitrage vs edges vs fill_risk, with fill-checking living in both polymarket_arbitrage and polymarket_fill_risk), so an agent must read long descriptions to avoid misselection.

Naming Consistency3/5

All names use snake_case and there are recognizable sub-families (get_* Bitcoin lookups, ask_pipeworx_*, polymarket_*), but conventions are mixed across the whole set: bare-noun state tools (block_height, hashrate, mempool_stats, mining_pools) sit beside verb_noun actions (get_block, list_subscriptions), and prefix placement is inconsistent (ask_pipeworx vs pipeworx_trending/pipeworx_feedback). The naming is readable but not predictable enough to guess a tool's name from its function.

Tool Count2/5

41 tools is well past the 25+ threshold for a coherent server, and the count is inflated by bundling two unrelated products under a server named after only the smaller half (~10 Bitcoin tools vs ~31 Pipeworx tools). Many Pipeworx tools are convenience wrappers around one universal router, adding surface area without adding genuinely new capabilities.

Completeness3/5

Each half is internally workable: the Bitcoin side covers blocks, transactions, addresses, fees, hashrate, and pools, while the Pipeworx side provides broad query, research, subscription, and memory lifecycles. However, there are notable gaps relative to each domain (no block-list/fee-history endpoints on the explorer side; no direct per-source CRUD on the data side), and no single coherent domain is fully served because the server's stated identity matches only a fraction of its tools.

Resources