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Glama

Gov Auctions

by io.github.pipeworx-io

Auction Lot Details

auction_lot_details
Read-onlyIdempotent

Full details for a single government auction lot, looked up by its source + source_lot_id (as returned by auctions_search) or by its listing URL. Returns title, description, category, location, bid, close time, seller agency, and link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoAlternatively, the full listing URL.
sourceNoLot source: govdeals | allsurplus | irs.
source_lot_idNoThe lot id within that source.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "source": "govdeals",
+    "source_lot_id": "12345678"
+  },
+  {
+    "url": "https://www.govdeals.com/api/auctions/12345678"
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate read-only, open-world, idempotent, and non-destructive behavior. The description adds value by enumerating the returned fields: title, description, category, location, bid, close time, seller agency, and link. No contradictions.

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?

Two sentences: first specifies purpose and lookup mechanisms, second lists return fields. No redundant information; every word is informative.

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?

For a single-lot lookup tool with well-documented parameters and annotations, the description covers essential context: what to provide, how to provide it, and what is returned. It doesn't discuss error handling or auth, but those are minor given the tool's simplicity.

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

Parameters4/5

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

Schema coverage is 100% with clear descriptions for each parameter. The description adds context by explaining the two lookup methods and the relationship between source/source_lot_id and url, which is not fully captured in the 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?

The description clearly states the verb 'get full details' for a resource 'single government auction lot', and specifies two distinct lookup methods: by source+source_lot_id or by URL. This distinguishes it from sibling tools like 'auctions_search' which returns lists.

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?

The description implies usage after a search by noting 'as returned by auctions_search', and offers URL as alternative. It does not explicitly state when not to use or name alternative tools, but the context is sufficient for an AI agent to infer appropriate use.

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

All Gov Auctions toolsInspect
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TDQS

A3.9/5.0
Disambiguation2/5

Several tools occupy nearly the same question-answering niche: ask_pipeworx, ask_pipeworx_beta (currently identical by its own description), ask_pipeworx_grounded, deep_research, and validate_claim are easy to confuse. The polymarket suite also has overlapping edge/arbitrage/fill-risk boundaries, and discover_tools/suggest_questions both serve onboarding. The verbose descriptions help, but the set as a whole creates real misselection risk.

Naming Consistency4/5

Most tools follow clear snake_case verb_noun or domain-prefix patterns (auctions_search, polymarket_edges, subscribe/unsubscribe, remember/recall/forget). Minor inconsistencies exist: auction_lot_details is singular while the auction group is plural, and polymarket_edges versus polymarket_edge_tracker breaks the prefix pattern slightly. Overall the naming is predictable and readable.

Tool Count2/5

36 tools is well above the 25-tool threshold and feels bloated for a server named 'Gov Auctions': only 5 tools actually concern auctions, while the rest are general Pipeworx research, prediction-market, memory, subscription, and utility tools. Even as a general data platform, the count is heavy and includes several overlapping meta-tools.

Completeness4/5

For the auction-specific surface, the set covers search, lot details, closing-soon, historical sold prices, and data coverage, which is a solid read-only lifecycle. The main gaps are non-critical: no auction-category browser, no auction-specific alert/subscription type, and no bidding workflow. The broad research/esolution tools fill in most adjacent data needs even if they dilute the server's stated focus.

Resources