# Agently Request > Use for Agently request-side setup and contracts: model settings, Prompt/input/output design, effect tuning, missing or redundant context, structured output, response reuse, streaming, session memory, embeddings, and retrieval within one request family. Review can be triggered by a developer's need to understand node behavior, not only by naming Prompt review. Use agently-design for cross-node data flow and model/Host ownership. - Skill: `agentera/agently-request` (Agent Skill, multi-file: 13 files) - Install (CLI): `npx skillmds@latest add agentera/agently-request` - Raw SKILL.md: https://api.skillmd.com/api/skills/agentera/agently-request/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: agentera (https://skillmd.com/u/agentera) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/agentera/agently-request --- # Agently Request Use this Skill when the work can be owned by one ModelRequest family. Use `agently-triggerflow` when a later semantic step needs a tool result, system lookup, approval, artifact readback, or host computation produced after the first request, or when branching, concurrency, retry, or pause/resume must stay visible in the application lifecycle. For multi-round Prompt collaboration, start each substantive round with current items (status first) and a timestamped, versioned change-log table. Use [Multi-Round Collaboration](../agently/references/multi-round-collaboration.md) to preserve pending decisions, modifications and abandonment. ## Read by Need - Provider, endpoint, environment, settings namespace, or connectivity: [model-setup.md](references/model-setup.md). - Request responsibility, effect tuning, input/output sufficiency or redundancy, collaborative review, Prompt config/references, reusable contracts or inheritance: [prompt-management.md](references/prompt-management.md). - Structured output, Pydantic, ensure/validation, streaming formats, or direct long-output delivery: [output-control.md](references/output-control.md). - Reusing one request result as text/data/meta or consuming its streams: [model-request-result.md](references/model-request-result.md). - Session continuity and durable memory: [session-memory.md](references/session-memory.md). - Embeddings, RecordStore, ContextSource, retrieval, and grounded citations: [knowledge-base.md](references/knowledge-base.md). - Cross-source progressive disclosure and real-world Skills: [context-and-skills.md](../agently/references/context-and-skills.md). ## Request Contract - Use collaborative review when request contracts can clarify model duties, improve execution effects, or reveal missing/redundant data; an explicit "Prompt review" request is unnecessary. Start complex reviews with a flow overview highlighting model nodes and Host handoffs, then group related Prompt tables for comparison. Up to three logical nodes may share a reply; tightly coupled larger groups are allowed. Prioritize developer understanding, not fixed counts or one-node approval turns. Preserve confirmation of consequential changes and distinguish design findings from measured effects. See `references/prompt-management.md`; use `agently-design` for cross-node flow/ownership analysis, not for unrelated mechanical work. - After measured schema/ensure/length failures, consider a shallower model-facing projection or coherent request splits with Host reconstruction and unchanged final validation. See `references/output-control.md`. - Keep a one-off fluent request readable as one chain: `.input(...)`, `.info(...)`, `.instruct(...)`, `.output(...)`, then its result call. Split only for actual reuse, independently owned configuration, or dynamic composition. - Do not promote literals or behavior from a single observed instance into normative prompt instructions. Derive a general invariant and test contrasting cases; use illustrative examples only to explain an already stated rule, and keep their total rendered content smaller than the non-example normative prompt. - Put runtime facts in `input`, authoritative evidence/API/schema material in `info`, behavior and transformation rules in `instruct`, and the exact downstream-consumed shape in `output`. - Define each consumed field's type, meaning, requiredness, enum/format/range, nullability, and cross-field constraints where applicable. - Give the model every non-sensitive satisfiable validator rule before the first attempt. Deterministic validation remains authoritative; retry feedback repairs a declared contract and must not become blind rule discovery. - Use ModelRequest structured output for prose-derived intent, routing, relevance, grading, and acceptance. Host code owns schema/type checks, authorization, arithmetic, offered-key membership, and side effects. - Combine semantic fields in one ordered response only when they share the same request-time evidence snapshot and later fields need no post-dispatch fact. Streaming cannot inject a tool or host result into an in-flight request. - Validate schema, offered keys, authorization, and deterministic constraints before a real call or side effect. For VLM requests, prefer `.image(question=..., file=...|url=...|files=[...]|urls=[...])`. Use `.attachment(...)` only when the caller owns provider-style mixed content or exact content ordering. ## Results, Context, and Memory - Direct ModelRequest calls return `ModelRequestResult`; Agent quick chains return `AgentExecutionResult`. Reuse the same result facade for text, parsed data, metadata, and streams instead of issuing the request again. - When no consumer needs progress, await the final getter directly. Treat `instant` fields as provisional UI or cancelable/idempotent preparation and reconcile them against the final validated result. - Session memory is not workflow state. `SessionMemory` owns extraction and compression policy; `RecordStore` owns durable records and retrieval; TriggerFlow execution state owns workflow progression. - Keep raw retrieval records cold. Give the model bounded task-relevant facts and one host-issued key per candidate, then validate and reconstruct canonical identities in host code. - For retrieval-backed answers, offer trusted `ref_id` values, require `[[ref:]]`, and resolve approved source cards/links host-side. ## Avoid - Handwritten provider HTTP, prompt templating, JSON repair, or retry loops before checking Agently settings and output contracts. - Moving a one-use schema or prompt step away from its request chain only to shorten the visible code. - Re-requesting the model separately for text, data, and metadata. - Treating retrieval hits, memory records, provisional stream fields, or model prose as deterministic proof of authorization or side effects. - Turning entity literals, one-time input or environment state, a historical incident, test fixture, or expected answer from one observed instance into a prompt branch, or letting illustrative examples create behavior that the normative contract never states.