agently-request✓ ناجح

محتوى SKILL.md

---
name: agently-request
description: "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."
---

# Agently Request

Use this skill when the work stays on the request side: provider setup, prompt
contracts, output contracts, response consumption, session continuity, or
retrieval.

If the owner layer is still unclear, start with `agently`. If the
request clearly needs branching, waiting, resume, or durable orchestration, use
`agently-triggerflow` and read this skill only for model-step details.

## Route Inside This Skill

- model endpoint, env vars, `${ENV.xxx}`, settings namespaces, or connectivity checks -> `references/model-setup.md`
- prompt slots, prompt config, YAML/JSON prompt files, mappings, or reusable request contracts -> `references/prompt-management.md`
- VLM image questions, local image files, image URLs, or multi-image input -> use `.image(question=..., file=...|url=...|files=[...]|urls=[...])`; keep `.attachment([...])` for low-level rich-content passthrough or exact mixed-content ordering
- stable fields, required keys, machine-readable output, `.output(...)`, `ensure_keys`, or validation -> `references/output-control.md`
- one response consumed as text/data/meta/stream without re-requesting -> `references/model-response.md`
- conversation continuity, memo, chat history, or restore-after-restart -> `references/session-memory.md`
- embeddings, Chroma collections, Workspace recall, retrieval, or KB-to-answer -> `references/knowledge-base.md`

## Native-First Rules

- keep provider settings outside prompt and workflow code; prefer settings files with `${ENV.xxx}` placeholders when deployment values differ by environment
- keep stable prompt and output contracts in prompt config when shared across a request family
- for VLM image requests, prefer `.image(question=..., file=...|url=...|files=[...]|urls=[...])`; use `.attachment([...])` only when the caller already owns provider-style rich content blocks
- use `.output(...)` tuple ensure flags for fixed required leaves; use runtime `ensure_keys` only for runtime-dependent paths
- order output fields from supporting information to final decision. Agently
  output schemas are ordered: evidence, assumptions, clarifications, source
  notes, calculations to perform, concise rationale, and rule checks should
  come before final booleans, verdicts, replies, summaries, or actions.
  User-facing rendering may reorder sections for natural reading, but the model
  generation contract should keep support-before-conclusion order.
- for grading, judging, evaluation, confidence, trust, usability, relevance, or
  quality tasks, ask the model for conceptual levels with explicit definitions
  instead of precise numeric scores. Use labels such as high_trust,
  moderate_trust, low_trust, excellent, adequate, weak, or failed, and define
  each label in the prompt. If downstream code needs statistics, thresholds,
  weighting, or index math, map the labels to deterministic numbers in code
  after model output; do not ask the model to emit `0.78`, `3/5`, or `8/10` as
  the primary judgment.
- do not ask the model to perform complex, long, or high-precision arithmetic,
  derivations, or data transformations directly. Ask it to produce executable
  Python, Bash, SQL, or another appropriate calculation plan, run that code with
  tools, then feed the original question, code, and observed result back into
  the next model step.
- when testing model-owned content, use an Agently model judge with output
  control and assert structured boolean rule judgments; avoid keyword,
  substring, regex, or snapshot checks as the primary semantic correctness test
- for scenario routing, intent detection, and business classification, use a
  model request with an Agently output schema instead of tokenization, word
  segmentation, keyword hits, or substring rules. Choose smaller or local models
  for simple decisions, and larger models for many labels, dense rules,
  ambiguity, or complex returned structures.
- use `get_result()` when the same result must be read multiple ways. Agent
  quick prompt chains return `AgentExecutionResult`; direct low-level
  ModelRequest calls return `ModelResponseResult`. `get_response()` remains a
  compatibility alias where present, but new Agent examples should prefer
  `get_result()`
- keep Session memory separate from TriggerFlow execution state
- use `workspace.build_context(...)` when ordinary multi-turn task work needs a
  ContextPack from prior Workspace records; use low-level `workspace.search(...)`
  for debugging or explicit filters
- when the next request should be produced by an Agent-owned task loop, let
  `agent.create_task(...)` build the ContextPack between iterations and record
  observations, decisions, verification, and checkpoints; do not duplicate that
  loop with ad hoc request retries
- use `workspace.get_data(...)`, `workspace.links(...)`,
  `workspace.latest_checkpoint(...)`, and `workspace.checkpoint_history(...)`
  when building explicit loops that store structured state and record lineage
- keep retrieval explicit when its results feed a later request or workflow step
- default to async-first response consumption in services, streaming paths, and workflows

## Anti-Patterns

- do not handwrite provider HTTP calls before checking native model requester settings
- do not rebuild prompt templates with ad hoc string formatting when prompt mappings fit
- do not handwrite JSON repair/retry loops before using output contracts and validation
- do not re-request the same model call only to get text, parsed data, or metadata separately
- do not hide retrieval inside unrelated prompt code

## Read Next

- `references/model-setup.md`
- `references/prompt-management.md`
- `references/output-control.md`
- `references/model-response.md`
- `references/session-memory.md`
- `references/knowledge-base.md`