agently
Use when a model-powered product, assistant, automation, evaluator, or workflow request still needs the right Agently owner, execution shape, or project boundary chosen. Also use for explicit low-frequency TaskDAG or DynamicTask requests.
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Structure
- Ships 26 executable scriptsassets/full-stack-reference/actions/__init__.py, assets/full-stack-reference/actions/growth.py, assets/full-stack-reference/actions/sandbox/__init__.py, assets/full-stack-reference/actions/sandbox/calculate_growth.py, assets/full-stack-reference/app.py, …. Review what they do before enabling the skill for agents with tool access.
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- The source hub's security checks flagged this skillSnyk: warn (Risk: MEDIUM · 1 issue)
SKILL.md
--- name: agently description: Use when a model-powered product, assistant, automation, evaluator, or workflow request still needs the right Agently owner, execution shape, or project boundary chosen. Also use for explicit low-frequency TaskDAG or DynamicTask requests. --- # Agently Start here when the request is expressed as product behavior rather than an Agently API. Choose the smallest native owner before choosing files or mechanisms. The request does not need to mention Agently. When an Agently developer needs to understand model-node duties, tune execution effects, check data flow or redundant context, or judge model/Host ownership, use collaborative review without waiting for the phrase "Prompt review". Route through `agently-design` for the highlighted flow and handoffs, and `agently-request` for related Prompt tables grouped by readability and dependency. Keep unrelated mechanical work outside this review method. For multi-round design, Prompt revision or experiment evaluation, begin each substantive round with a status-left/item-right table and a timestamped, versioned change-log table. Follow [the collaboration record guidance](references/multi-round-collaboration.md). ## Workflow 1. Reduce the request to goals, inputs, outputs, side effects, evidence, and lifecycle needs. 2. Separate model-owned semantic decisions from host-owned validation, authorization, identity joins, arithmetic, and effects. 3. Assign each decision, state, and effect to one existing owner. 4. For non-trivial flows, map nodes, value/event edges, invariants, and the production need for every requested field and stage. 5. Implement async-first where the caller owns an async boundary; validate deterministic contracts separately from model-owned quality. 6. Report a framework gap when no native owner can carry a required invariant. Do not hide the gap behind business-specific glue or a pass-through facade. ## Route by Owner - One request family—provider setup, prompt, structured output, LongContent, auto_continue, TTS/STT audio, result reuse, session memory, embeddings, or retrieval—uses `agently-request`. - AgentExecution plugins, final policies, Actions, Shell, MCP, ExecutionResource, TaskWorkspace, RecordStore, service exposure, RuntimeEvent, or DevTools uses `agently-runtime`. - Process-local task lifetime, sync/async bridging, loop-neutral handles, settlement, replay channels, or local listeners uses `agently-stage`. - Cross-owner architecture, request/value/event topology, evidence and identity boundaries, lifecycle, pressure, or information-loss audit uses `agently-design`. - Developer-owned progression, branching, concurrency, approval, wait/resume, retry, or restart-safe orchestration uses `agently-triggerflow`. - Migration from LangChain, LangGraph, LlamaIndex, CrewAI, or a similar system uses `agently-migration`. - Explicit model-generated or application-submitted acyclic DAG data is a low-frequency advanced case. Keep it here and read `references/task-dag.md`; do not introduce TaskDAG for ordinary Agent or workflow work. ## Read by Need - Conditional project shapes and the full-stack reference asset: `references/project-framework.md`. - TaskContext, ContextReader, TaskWorkspace, RecordStore, SkillLibrary, and the SkillsExecutor compatibility facade: `references/context-and-skills.md`. - Submitted TaskDAG data and the DynamicTask convenience facade: `references/task-dag.md`. - Simulation-first and real-model validation: `references/model-quality-validation.md`. - Cross-layer topology audit methods live in `agently-design`, especially its `../agently-design/references/execution-topology-validation.md`. ## Core Ownership Rules - `ModelRequest` owns one model interaction and its prompt/output contract. - `AgentExecution` owns one Agent run and its selected producer, controls, result and streams. In 4.1.4.8, `request`, `plan`, `long_content` and `long_task` are plugins; read the runtime Skill's [execution contract](../agently-runtime/references/agent-execution.md). - `agent.create_task(...)` returns a long-task AgentExecution draft. Its producer owns planning, evidence and replan; released AgentTask imports remain compatible. - `AudioModelRequest` owns independent TTS/STT drivers. Agent audio calls and audio-dependent Execution plugins require an explicit audio binding. - `ActionRuntime` owns model-callable operations; `ExecutionResource` owns live dependency lifetime. - `TriggerFlow` owns application-visible orchestration and runtime signals. - `TaskContext` owns task information and creates consumer-bound readers; `TaskWorkspace` owns files; `RecordStore` owns durable records and recovery; `SkillLibrary` owns immutable installed Skill revisions. - `Agently.skills_executor` is management/context compatibility only. Do not recreate the removed generic Workspace, ContextBuilder, SkillsManager, Skills route/strategy, `skill_activation`, or `workspace_operation` owners. ## ModelRequest Boundary For output that must satisfy a downstream interface: - runtime facts go in `.input(...)`; - authoritative schemas, signatures, and source facts go in `.info(...)`; - transformation and call rules go in `.instruct(...)`; - the exact consumed shape goes in `.output(...)`. Declare the type, semantics, requiredness, enum/format/range, nullability, and cross-field constraints for every consumed field. Let a structured ModelRequest own prose-derived intent, routing, planning, relevance, or quality judgment; let host code validate bounded enums/keys and perform effects. Do not request hidden chain-of-thought. A bounded process field is justified only when it has a named role, bounds, consumer, retention rule, and failure behavior. ## Project and Validation Gate Start one-request applications with composition, settings, the prompt contract, and tests. Add workflows, services, Actions, local Skills, utilities, or resources only for a current owner and consumer. A logical node is not automatically a file or class. Deterministic tests prove schemas, identities, lifecycle, accounting, file or record effects, and safety. Semantic quality needs declared criteria and a structured coding-agent, model, or human review. Classify criticality (hard gate or soft target) separately from evaluation method (deterministic or semantic). For real-model claims, define criteria first, label simulations honestly, use the smallest authorized representative run, and record raw facts separately from judgment. Real traces override simulated expectations. ## Anti-Patterns - Custom parsers, retry managers, state stores, or schedulers before checking the native owner. - Keyword, substring, regex, tokenization, or hand-written score tables as the semantic owner. - Unconsumed output fields, request stages, wrappers, or project directories. - All-serial complex flows without dependency analysis. - Full source, identity-heavy records, or raw metadata copied into every prompt. - Canned answers, hidden expected-answer fixtures, or test-only production branches presented as framework capability evidence.