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kopern_run_grading

Run a grading suite on an agent. Executes all test cases, evaluates with configured criteria, returns detailed scores. Uses YOUR API keys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYesThe agent ID or name
suite_idYesThe grading suite ID

TDQS

A4/5.0
Behavior4/5

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

The annotations are minimal (readOnlyHint=false, openWorldHint=true), so the description adds meaningful context by disclosing that the tool executes test cases, evaluates, returns detailed scores, and 'Uses YOUR API keys'—an important external side-effect. It does not describe persistence or cost details, but it goes beyond the annotations without contradicting them.

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 two short sentences, front-loaded with the primary purpose, and every clause contributes meaning. It avoids redundancy with the schema and is easy to parse quickly.

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 simple two-parameter tool, the description covers the main action and return value ('detailed scores') and includes the key caveat about API key usage. It does not describe output structure, but since no output schema is present and siblings cover related retrieval, this is reasonably complete.

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 schema already provides 100% coverage for both parameters with clear descriptions for agent_id and suite_id. The tool description does not add extra parameter-level semantics (e.g., formats, constraints, or usage patterns), so the baseline of 3 is appropriate.

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 a specific action ('Run a grading suite') and target ('an agent'), and distinguishes itself from siblings like get_grading_results (retrieval) and create_grading_suite (creation). The phrase 'Executes all test cases, evaluates with configured criteria, returns detailed scores' nails the scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool—when you need to execute a grading suite—but it does not explicitly contrast with alternatives such as kopern_get_grading_results for retrieving results or kopern_list_grading_runs for listing runs. It provides some context via 'Uses YOUR API keys' but lacks explicit when/when-not guidance.

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

A3.7/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (create vs list vs get vs run vs connect). A few potential overlaps exist (deploy_template vs create_agent, import_agent vs create_agent, grade_prompt vs run_grading) but descriptions clarify the differences.

Naming Consistency4/5

All tools share the 'kopern_' prefix and mostly follow a verb_noun pattern (create_*, get_*, list_*, run_*, connect_*). The exception is 'kopern_compliance_report', which uses a noun phrase without a verb, breaking the otherwise consistent naming.

Tool Count2/5

With 31 tools, this exceeds the 25-tool threshold for well-scoped servers. While the domain is broad (agent lifecycle, grading, pipelines, teams, connectors), the sheer number of tools feels heavy and could be consolidated (e.g., a single 'manage_memory' tool already bundles multiple actions).

Completeness3/5

Core agent management (create, read, update, delete, list) is solid, and grading has suite creation, execution, and results. However, pipelines and teams lack get/update/delete operations, connectors only support connect (no disconnect), and there's no way to manage grading suites beyond creation and running. This leaves notable gaps for secondary resources.

Resources