legacy/v1/skills/agently-model-response/SKILL.md
Use when the user wants to reuse one model result, read text/data/meta without re-requesting, or stream partial updates, including `get_response()`, async getters, `delta`, `instant`, and `specific`.
npx skillsauth add agentera/agently-skills agently-model-responseInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill when the output contract is already chosen and the remaining issue is how the response instance should be consumed or reused.
The user does not need to say get_response(). Requests to reuse one result as text, parsed data, metadata, or progressive updates should route here.
get_response() when one request result must be consumed more than oncedelta, instant, specific, or all instead of custom stream splitting logicinstant or streaming_parse already fitsreferences/overview.mdtools
Use when the user wants to build, initialize, validate, optimize, or refactor a model-powered assistant, internal tool, automation, evaluator, or workflow from a business scenario or common problem statement, including project-structure refactors or starter skeletons that may separate model setup, prompt config, and orchestration, even if the request also mentions a UI, app shell, or local model service such as Ollama, and it is still unclear whether the solution should stay a single request, add supporting capabilities, or become orchestration. The user does not need to mention Agently explicitly.
data-ai
Use when the user needs Agently TaskDAG / Dynamic Task, model-generated or app-submitted DAG planning, TaskDAG validation, DynamicTaskResolver handlers, TaskDAGExecutor execution, or the Agently.create_dynamic_task compatibility facade. TaskDAG is the DAG foundation capability; Dynamic Task is the convenience facade over it and uses TriggerFlow as the execution substrate.
tools
Use when the user wants Agently runtime extension capabilities: Action Runtime, built-in action packages, legacy tool compatibility, MCP access, Execution Environment lifecycle, FastAPIHelper or streaming API exposure, auto-function helpers, KeyWaiter, or optional agently-devtools observation, evaluation, and playground integration.
development
Use when the user is shaping Agently request-side behavior: model setup, settings files, prompt management, structured output, response reuse, streaming consumption, session memory, embeddings, knowledge-base indexing, retrieval, or retrieval-backed answers within one request family.