rubrkit_read_evalRead one eval run, including the stats statistical verdict on advanced-mode runs (empty for standard runs). Requires artifact_bundles:read for API keys.
| Name | Required | Description | Default |
|---|---|---|---|
| evalRunId | Yes | ||
| artifactBundleId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that 'stats' are only available for advanced-mode runs and empty for standard runs, which is a key behavioral detail. It also mentions the required permission. It does not, however, describe error handling or response format, but the given details are above average.
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 long, front-loads the core purpose and key behavioral nuance about stats, and adds a permission note. Every sentence adds value with no redundancy.
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?
No output schema exists, so the description should clarify return values. It mentions 'stats' but not other potential fields (e.g., basic eval data). For a simple read operation, this may be adequate, but it leaves ambiguity about the full response structure. Given the lack of schema, a bit more detail would improve completeness.
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 description coverage is 0%, so the description must compensate. It does not explain the meaning or purpose of 'evalRunId' or 'artifactBundleId' beyond stating they are required. No additional context is provided, making it hard for the agent to infer how to obtain these IDs.
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?
Description clearly states the tool reads one eval run and specifies the inclusion of 'stats' for advanced-mode runs. It uses a specific verb ('Read') and resource ('eval run'), and distinguishes from sibling tools like 'rubrkit_list_evals' and 'rubrkit_run_evals' by focusing on a single run with statistical details.
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 description provides a prerequisite ('Requires artifact_bundles:read for API keys'), but does not explicitly state when to use this tool versus alternatives like 'rubrkit_list_evals' or 'rubrkit_run_evals'. It lacks guidance on when not to use it or how the stats behavior relates to typical workflows.
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.
Most tools target distinct resource-action pairs, and descriptions clarify differences like soft vs hard delete or list bundles vs list versions. However, some names are similar (e.g., delete_artifact_bundle vs hard_delete_artifact_bundle), which could cause minor confusion.
All tools follow a uniform rubrkit_verb_noun pattern with imperative verbs and snake_case, making them predictable and easy to navigate. No mixed conventions or inconsistencies.
With 30 tools, the server is comprehensive but slightly heavy for a single-purpose MCP. The tools cover multiple sub-domains (bundles, files, audits, evals, conversions, docs), which justifies the count, but consolidation could reduce complexity.
The set covers CRUD for artifact bundles, file operations, audit/eval lifecycle, and API documentation. Minor gaps include missing bundle metadata update and file deletion, but core workflows are supported.