get_packageMetadata for a single package by packageId (e.g., "BILLS-118hr1234ih", "FR-2024-05-12"). Returns title, dates, citations, granule count, download links (PDF/XML/MODS).
| Name | Required | Description | Default |
|---|---|---|---|
| package_id | Yes | GovInfo packageId |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "package_id": "BILLS-118hr1234ih"
+ },
+ {
+ "package_id": "FR-2024-05-12"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "Package metadata including title, dates, citations, and download links",
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds useful behavioral context by enumerating the returned data (title, dates, citations, granule count, download links). No contradictions 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and then lists return items succinctly. Every word earns its place; no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a single parameter, full schema coverage, an output schema present, and comprehensive read-only/idempotent annotations, the description is complete for the tool's simplicity. It covers the operation, input examples, and output highlights, leaving no critical gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by providing concrete examples of valid package_id formats ('BILLS-118hr1234ih', 'FR-2024-05-12'), which clarifies the expected string format beyond the schema's generic 'GovInfo packageId'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies a clear verb+resource: 'Metadata for a single package by packageId', and distinguishes from siblings like get_granule (granules) and search_packages (search). Concrete examples of package IDs further clarify the target resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a single package by packageId' establishes clear context for when to use this tool: when you have a specific package identifier and need its metadata. It does not explicitly name alternatives or exclusions, but the single-package focus implicitly distinguishes it from search/list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all serve lookup/discovery in similar ways, and the five polymarket_* tools plus bet_research blur together. The six genuinely GovInfo-specific tools are distinct, but an agent would struggle to pick between the numerous meta and market tools, especially when the server is supposed to be about government information.
Most tools follow a readable verb_noun pattern (list_collections, search_packages, get_granule, resolve_entity), but there are deviations: domain-prefixed nouns like polymarket_arbitrage, noun-ish names like pipeworx_trending, and verb phrases like ask_pipeworx_beta or generate_llms_txt. Overall it is mixed yet still navigable, not chaotic.
36 tools is excessive for a server named Govinfo: only about six tools (list_collections, search_packages, get_package, list_granules, get_granule, search_within) actually serve that domain, while the remaining ~30 are Pipeworx meta-tools, prediction-market helpers, memory utilities, and AI-visibility checks. The count is bloated relative to the apparent scope and dilutes the server's identity.
The core GovInfo workflow is present — list collections, search packages, fetch package metadata, list and fetch granules, and semantically search within fetched text. However, there is no tool that directly downloads or returns the full text/PDF/XML content of a package or granule; agents only get links, so a full-document workflow requires an external fetch. The unrelated tools do not fill that gap and instead distract from the domain.