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Glama

Govinfo

by io.github.pipeworx-io

List Granules

list_granules
Read-onlyIdempotent

List granules within a package — e.g., sections of a CFR title, individual entries in a Federal Register issue. Returns granule IDs + titles.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoAlias for page_size, 1-100.
page_sizeNoGranules per page, 1-100 (default 100). `limit` works as an alias.
package_idYesGovInfo packageId
offset_markNoPagination cursor

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
totalYesTotal granules in package
granulesYesList of granules in package
returnedYesNumber of granules returned
package_idYesGovInfo package ID
next_offset_markNoPagination cursor for next results

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / limit
      Added value: +{
+  "description": "Alias for page_size, 1-100.",
+  "type": "number"
+}
    • changedInput schema / properties / page_size / description
      Previous value: -"1-100 (default 100)"New value: +"Granules per page, 1-100 (default 100). `limit` works as an alias."
  2. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "package_id": "BILLS-118hr1234ih"
+  },
+  {
+    "package_id": "CFR-2024-title29-vol5",
+    "page_size": 50
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "granules": {
+      "description": "List of granules in package",
+      "items": {
+        "properties": {
+          "class": {
+            "description": "Granule class/type",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "id": {
+            "description": "Granule ID",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "link": {
+            "description": "URL to granule on GovInfo",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "title": {
+            "description": "Granule title",
+            "type": [
+              "string",
+              "null"
+            ]
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "next_offset_mark": {
+      "description": "Pagination cursor for next results",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "package_id": {
+      "description": "GovInfo package ID",
+      "type": "string"
+    },
+    "returned": {
+      "description": "Number of granules returned",
+      "type": "number"
+    },
+    "total": {
+      "description": "Total granules in package",
+      "type": "number"
+    }
+  },
+  "required": [
+    "package_id",
+    "total",
+    "returned",
+    "granules"
+  ],
+  "type": "object"
+}
  3. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, so the description only needs to add value beyond that. It adds conceptual context about what granules are and what the call returns, though it does not mention pagination behavior despite pagination parameters existing.

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?

The description is a single, information-dense sentence with front-loaded purpose, concrete examples, and a return-value note. There is no wasted text or repetition of schema content.

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 output schema and fully described input schema, plus safety annotations, the description is complete enough for correct tool selection. It explains the domain concept (granules) and the output shape at a high level; pagination details are already available in the schema and output schema.

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

Parameters3/5

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

The input schema covers 100% of parameters with descriptions, so the baseline is 3. The description adds no parameter-level detail beyond saying the operation is within a package, but it does not need to compensate for any schema gaps.

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 uses a specific verb and resource ('List granules within a package') and clarifies what counts as a granule with concrete examples from CFR titles and Federal Register issues. It also states the return payload (granule IDs + titles), which distinguishes it from sibling tools like get_package or get_granule.

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 gives a clear use context: call this when you already have a package_id and want the granules inside it. It does not explicitly name alternatives or when-not-to-use cases, but the context is strong enough for an agent to select it over search/list siblings.

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

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TDQS

A3.8/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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.

Tool Count2/5

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.

Completeness3/5

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.

Resources