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TsvetanG2

cognigy-ai-mcp-management-server

list_function_instances

Read-onlyIdempotent

Retrieve execution history and status of a Cognigy function. View running and completed instances with results.

Instructions

Lists running and completed instances of a Cognigy.AI Function. Shows execution history, status, and results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNoNumber of items to skip for pagination
limitNoMaximum number of instances to return (default: 25, max: 100)
functionIdYesThe function ID to list instances for
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe, read-only operation. The description adds that it 'shows execution history, status, and results', which provides some behavioral context but does not go beyond what the annotations imply. No contradictions.

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 concise sentences that are front-loaded with the primary purpose. Each sentence adds value without redundancy. No wasted words.

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?

Given the tool's low complexity (3 parameters, no enums, no output schema), the description adequately conveys the tool's purpose and what it returns. However, it could benefit from mentioning that the output includes a list of instances with status and results, but since there is no output schema, this is a minor gap.

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?

Schema description coverage is 100%, with clear documentation for all three parameters (skip, limit, functionId). The description does not add further semantic meaning beyond what the schema provides, so baseline 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 uses the specific verb 'Lists' and clearly identifies the resource as 'running and completed instances of a Cognigy.AI Function'. It explicitly mentions execution history, status, and results, distinguishing it from sibling tools like 'list_functions' or 'trigger_function'.

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 usage for retrieving instance data for a function, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., 'get_function_instance' for a single instance, or 'stop_function_instance' for stopping). No exclusion criteria or context is given.

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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