jbaruch/koog
Koog 1.0 idioms, gotchas, and scaffolding skills for Kotlin agents on the JVM
87
88%
Does it follow best practices?
Impact
87%
1.85xAverage score across 45 eval scenarios
Advisory
Suggest reviewing before use
task.mdevals/scenario-3/
Delegate Heavy Analysis to a Remote Agent
Problem/Feature Description
A developer has a Koog 1.0 agent that handles most user questions locally with a small model. For a small subset of questions that require a much larger model (deep code analysis), a separate team runs a "specialist" agent on their own infrastructure. The specialist exposes an A2A endpoint at https://analyst.team.example/a2a; auth is via a bearer token in ANALYST_API_TOKEN.
The developer wants the local agent's LLM to decide when a question is heavy enough to deserve the remote specialist, and delegate by calling the remote as if it were a tool.
Output Specification
Walk through how to wire the remote A2A endpoint as a callable surface. Produce the relevant code and Gradle changes as a single response, labeled.
evals
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scenario-45
skills
add-observability
add-persistence
add-rag
add-structured-output
add-token-budgeting
add-tool
cache-llm-calls
define-prompt
domain-model-subtask-pipeline
references
enable-prompt-caching
handle-agent-events
manage-state
migrate-from-0-x
model-planner-subtasks
persist-chat-history
query-sql-from-agent
scaffold-agent
snapshot-and-restore
test-koog-agents
trace-agent-internals
use-attachments
use-functional-agent
use-llm-node-variants
use-planner
wire-a2a
wire-acp-server
wire-ktor-server
wire-mcp-server
wire-spring-boot