legacy/v1/skills/agently-output-control/SKILL.md
Use when the user wants stable structured fields, required keys, value-level output validation, reliable machine-readable sections, or downstream-consumable output from one model request, including prompt-config-owned output contracts, `.output(...)`, tuple ensure flags, runtime `ensure_keys`, `.validate(...)`, and structured streaming.
npx skillsauth add agentera/agently-skills agently-output-controlInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill when the question is what shape the model should return and how that shape should stay reliable.
The user does not need to say .output(...), tuple ensure, ensure_keys, or .validate(...). Requests for stable JSON-like fields, structured reports, or machine-readable sections should route here.
.request.output when the schema is stable and shared across a request family.output(...) for machine-readable results when the schema is dynamic, exploratory, or easier to keep close to code4.1.0.1+, prefer tuple ensure in .output(...) for fixed required leavesensure_keys only when the required path is runtime-dependent, conditional, or awkward to express in the static schema.validate(...) or validate_handler= when the field exists but the value still needs business validation.output(...) already owns the contractensure or, when necessary, runtime ensure_keysensure or ensure_keys with value checks that belong in .validate(...)references/overview.mddevelopment
Use when the user needs Agently Dynamic Task, model-generated or app-submitted DAG planning, TaskDAG validation, DynamicTaskResolver handlers, or TaskDAGExecutor execution through Agently.create_dynamic_task. Dynamic Task is a first-class Agently API that uses TriggerFlow as an 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.
development
Use when the user needs workflow orchestration such as branching, concurrency, approvals, waiting and resume, runtime stream, restart-safe execution, mixed sync/async function or module orchestration, event-driven fan-out, process-clarity refactors that make stages explicit, performance-oriented refactors that collapse split requests, or workflow definitions and chunk-level runtime metadata that must stay visible for debugging and visualization. The user does not need to say TriggerFlow explicitly.