agently-runtime

Agently Runtime

Use this Skill after the request or workflow owner is known. Use agently-triggerflow when branching, concurrency, pause/resume, retry, or multi-stage progression must remain visible in the execution graph. Use agently-stage only for process-local lifetime and sync/async bridging.

Read by Need

• Execution selection, nested producers, run/rework/control, final validate, artifact/review, or declared Agent capabilities: agent-execution.md.
• Callable Actions, Search/Browse, MCP/ACP, policy, artifacts, or AgentTask evidence: actions-runtime.md.
• Action versus ExecutionResource, managed clients/sandboxes/processes/ browsers/databases, Shell/BashExecutor, PowerShell, offline/online/host profiles, approval, and streaming process I/O: actions-execution-resource.md.
• auto_func, KeyWaiter, FastAPIHelper, SSE, or WebSocket exposure: helpers-and-services.md.
• RuntimeEvent, logs, traces, evaluation, playground, or DevTools: devtools.md.
• Evidence-backed reviewer comments, Coding Agent responses and rerun comparison: devtools-review.md. Requires DevTools 0.2; check the API capability before using its writeback steps.
• TaskContext, ContextReader, SkillLibrary, and real-world Skill packages: context-and-skills.md.

Owner Boundaries

Do not collapse these into a generic Workspace or runtime manager. File space is not record storage; records are not model-hot context; a Skill package is not an executor or permission grant.

Runtime Rules

• Prefer @agent.action_func and agent.use_actions(...). The tool_* and use_tool(s) names are compatibility surfaces.
• Treat Action ids and model-planned arguments as untrusted. Validate schema, authorization, and policy before dispatch; require recorded Action evidence for claimed side effects.
• Keep permission profiles explicit and narrow. Do not expose shell, network, browser, install, file-write, or MCP capabilities merely because an AgentTask exists.
• Use TaskWorkspace for contained file work and verified artifact readback; use RecordStore for durable records and recovery. Keep large bodies cold behind refs until an explicit consumer reads them.
• A real-world Skill supplies guidance and addressable resources. Actions, MCP, ExecutionResources, script authorization, and side-effect proof remain explicit host-owned bindings.
• Use a fresh agent.create_execution() for multi-statement setup or an unrelated new request. A completed revision is immutable; explicit producer rework advances the same execution while old result readers retain their revision. See the execution contract above.
• In 4.1.4.8, select request, plan, long_content, or long_task through create_execution(...). Final .validate(handler) is a hard output gate; .review(..., on_fail="warn" | "block") is a soft assessment with an explicit terminal policy. Review does not silently rework; rework belongs to the producer. .artifact(...) requires verified TaskWorkspace readback.
• Use agent.create_task(...) only when the model should own bounded planning, execution evidence, verification, and replan. create_task_loop(...) is a compatibility spelling, not the recommended surface. Stable application orchestration belongs to TriggerFlow.
• Persist resource descriptors, never live clients or secrets. Reconstruct resources through their provider/resolver during recovery.
• Bind RuntimeEvent persistence explicitly. Availability of a RecordStore does not turn every observation into a durable event archive.
• Observation and transport are adapters: they must not become owners of routing, authorization, workflow lifecycle, semantic acceptance, or retry.

Fail Closed

Reject unknown Skill revisions, resource refs, Action ids, selection keys, context block keys, recovery providers, and external-resume identities. Offer models one short host-issued selection key, validate it against the offered set, then reconstruct canonical records in host code.

Do not use keyword or regex matching as the semantic owner for intent, Skill relevance, route choice, evidence usefulness, or output quality. Do not fake model-owned success with canned outputs or deterministic business mappings.