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Glama

Httpstatus

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 read-only, idempotent, non-destructive. Description adds specifics: for companies, it pulls latest 10-K metrics from SEC EDGAR/XBRL with correct fiscal-year handling; for drugs, it pulls FAERS and FDA trial counts. Also notes result sorting and citation URIs.

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?

Well-structured, starting with example queries then detailing functionality per type. Slightly lengthy but every sentence adds value; could be more concise but remains efficient.

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?

No output schema, but description explains return format (paired data + citation URIs), covers both entity types thoroughly, addresses edge cases (off-calendar fiscal years), and explains sorting behavior.

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 description adds significant context: explains what each 'type' enum returns, gives examples for 'values' (tickers vs drug names), and notes max/min constraints beyond schema descriptions.

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?

Clearly states side-by-side comparison of 2-5 companies or drugs in one parallel call. Provides specific user query examples ('compare X and Y', 'rank these companies') and contrasts with sequential 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 says 'ALWAYS PREFER over sequential single-pack lookups when comparing entities.' Includes example triggers and mentions sorting for 'largest/most/biggest' queries, providing clear when-to-use guidance.

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

All Httpstatus toolsInspect
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TDQS

A3.7/5.0
Disambiguation4/5

Most tools have distinct purposes, but ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are very similar, causing potential confusion. The memory tools (remember/recall/forget) are separate, but the overall set is diverse enough that agents can typically distinguish them.

Naming Consistency2/5

Tool names use a mix of camelCase (ask_pipeworx, entity_profile, generate_llms_txt) and snake_case (http_status, list_http_statuses, list_subscriptions), with no consistent verb_noun pattern. Some names are descriptive, but the lack of a unified convention hurts predictability.

Tool Count2/5

33 tools is high for a server named 'Httpstatus' that only has two HTTP-related tools. The large number spans data retrieval, memory, subscriptions, prediction markets, and more, making the server feel bloated and unfocused.

Completeness3/5

The server covers many domains but each is incomplete. HTTP status has lookup and list but no lifecycle. Memory tools are basic. Data retrieval is extensive but not exhaustive for any single domain. It's a broad but shallow collection.

Resources