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From invoke-agent
Retrieve and show agent output by output-id. Use when the user wants to view the result of a previous invoke-agent prompt call using the output ID that was returned.
How this skill is triggered — by the user, by Claude, or both
Slash command
/invoke-agent:outputThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Retrieve and display stored agent output by its output ID. After running `invoke-agent prompt`, the command returns an output ID; use this skill to view that output (stdout, stderr, file content, exit status).
Retrieve and display stored agent output by its output ID. After running invoke-agent prompt, the command returns an output ID; use this skill to view that output (stdout, stderr, file content, exit status).
Available substitutions: $ARGUMENTS or $0 — the output ID (e.g. /invoke-agent:output abc-123). See Skills docs.
Get the output ID from the user — the ID that was printed when they (or a previous step) ran invoke-agent prompt. When invoked with an argument, use $ARGUMENTS or $0 as the output ID.
Determine the DB path: If INVOKE_AGENT_DATABASE_PATH is set, the CLI picks it up automatically and no --db flag is needed. Otherwise, pass --db <project-root>/.invoke-agent/communication.db, where <project-root> is the directory where the AI agent CLI (e.g. Claude Code) was originally started — you already know this from your session context.
Run in the terminal:
invoke-agent output get <OUTPUT_ID> --json
# or, if INVOKE_AGENT_DATABASE_PATH is not set:
invoke-agent output get <OUTPUT_ID> --json --db <project-root>/.invoke-agent/communication.db
The command prints stdout, stderr, fileContent (if any), and statusCode for that output in JSON format.
npx claudepluginhub powdream/claude-plugins --plugin invoke-agentBuilds multi-step LLM agents with tool loops, conversation history, skills, structured output, and stateful conversations using Output AI SDK's Agent class.
Provides standardized Markdown templates for research, planning, implementation, and review agent outputs. Use when generating or parsing agent responses in autonomous dev workflows.
Guides adding try-catch console logging for successes, errors, and state to make app behavior visible to AI agents in debugging and agentic coding workflows.