versionsList available versions.
| Name | Required | Description | Default |
|---|---|---|---|
| module_path | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| versions | Yes | List of available version strings | |
| module_path | Yes | The module path |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "module_path": "github.com/sirupsen/logrus"
+ },
+ {
+ "module_path": "github.com/google/uuid"
+ }
+]Output schema / (root)Previous value: -nullNew value: +{
+ "description": "List of available versions for a Go module",
+ "properties": {
+ "module_path": {
+ "description": "The module path",
+ "type": "string"
+ },
+ "versions": {
+ "description": "List of available version strings",
+ "items": {
+ "type": "string"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "module_path",
+ "versions"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds no extra behavioral context (e.g., rate limits, constraints). It is consistent but does not surpass annotation coverage.
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 extremely concise but lacks structure. While it avoids verbosity, it could be improved by adding a brief explanation of the parameter or result format.
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?
Given a single required parameter and an existing output schema, the description is too minimal. It fails to describe what 'available versions' means, how the parameter is used, or any edge cases.
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?
The only parameter 'module_path' has no description in the schema (0% coverage) and is not explained in the tool description. The agent receives no semantic guidance beyond the parameter name.
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 'List available versions' clearly states the action (list) and the resource (versions). It is specific enough, though it does not differentiate from the sibling 'version_info' tool.
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?
No guidance is provided on when to use this tool versus alternatives (e.g., version_info). The description lacks context about prerequisites or appropriate scenarios.
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.
Several tool families overlap heavily: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical entry points, while discover_tools/suggest_questions and entity_profile/compare_entities/recent_changes serve similar discovery/comparison roles. The polymarket_* cluster also has tightly related boundaries that require reading long descriptions to disambiguate, and version-related helper tools (go_mod, module, versions, version_info) add further confusion.
Most tools follow a lowercase snake_case verb_noun pattern (list_subscriptions, resolve_entity, validate_claim), but there are notable deviations: bare verbs like remember/recall/forget, noun-only names like go_mod, module, versions, and version_info, and brand-prefixed names like ask_pipeworx and pipeworx_feedback. The naming is readable and generally predictable, yet the mix of conventions keeps it from being highly consistent.
With 35 tools, the surface is heavy for what is ultimately a data-access and research server. Many tools are conveniences or meta-wrappers that could be consolidated (e.g., three ask_pipeworx variants, multiple polymarket scanners, several onboarding/discovery tools). While the breadth is intentional, 35 feels bloated rather than well-scoped.
The toolset covers a remarkably broad domain: universal data lookup, grounded fact-checking, entity resolution, company profiles, comparisons, prediction-market analysis, memory, subscriptions, and feedback. Minor gaps exist—subscriptions can be created/cancelled but not updated/paused, and there is no direct resolver for pipeworx:// citation URIs—but these are workable and core workflows have no dead ends.