agentic-workflow-first

name	agentic-workflow-first
description	Start new work as a deterministic workflow of agentic steps, prompts, and tools instead of code. Use when designing a feature, deciding how to build something, choosing code vs recipe, or asking "how should I structure this".
metadata	{"version":"1.0","author":"amplihack"}

Agentic-Workflow-First

Purpose

Steer new work toward deterministic workflows made of agentic steps (prompts) + tool calls + a thin deterministic rail, and away from imperative code. Judgment belongs in prompts; side effects belong in tools; code is only glue.

When I Activate

I load when you mention: designing or structuring a feature, "how should I build this", "should this be code or a recipe", starting new work, "make this agentic", or "reduce the code".

The Rule (why this skill exists)

Most core functionality should be a collection of deterministic workflows with agentic steps, prompts, and access to tools — NOT code. Rust is only a thin deterministic rail.

Default behavior is to write code. This skill forces the opposite default: prove a step cannot be a prompt or a tool before you write imperative logic for it.

The 6-Step Decision Procedure

Follow these in order for any new piece of work.

Step 1 — Restate as goal + observable success criteria

Write the desired behavior as a single goal sentence and a numbered list of observable, verifiable success criteria (what a passing run produces). If you cannot state how to observe success, you are not ready to design.

Step 2 — Decompose into a deterministic workflow

Break the goal into an ordered (or branching) sequence of steps. Each step has one responsibility and a named output. This ordered set IS the workflow.

Step 3 — Classify every step (the core test)

Tag each step as exactly one of:

• (a) Agentic step — an LLM/agent reasoning step driven by a prompt. Choose this whenever the step requires judgment, classification, prioritization, interpretation, or open-ended decision.
• (b) Tool call — a deterministic capability with a side effect: CLI, API, file IO, git, gh. Choose this for anything with an external effect or a single correct deterministic result.
• (c) Thin rail — minimal glue code: typed-record IO, guardrails, attempt caps, fail-closed reads. Choose this ONLY for plumbing that is neither judgment nor an external capability.

Classification test — apply literally:

• Does the step decide something a reasonable person could disagree on? → (a).
• Does the step change the world or read one true value (write a file, call gh, run a command)? → (b).
• Is it pure plumbing moving typed data between (a) and (b) with guardrails? → (c).
• If tempted to write a Rust classify() / orient() / decide() / prioritize() function → it is judgment → it MUST be (a) behind a prompt.

Step 4 — Express the workflow as a recipe

Write the workflow as a recipe YAML (repo format — see templates.md). Agentic steps use type: "agent" with a prompt: block; tools use type: "bash". Data flows between steps as typed records (a file/JSON schema written by one step, read fail-closed by the next) — NEVER by scraping/parsing another step's stdout prose.

Step 5 — Write code only for the thin rail

Write imperative code ONLY for step-type (c), and only for what genuinely cannot be a recipe/prompt/tool. For every line of imperative judgment, write a one-line justification of why it is not an agentic step. If you cannot justify it, convert it.

Step 6 — Enable + verify end-to-end

The workflow must be runnable and observable. Run it, confirm each success criterion from Step 1 is produced, and confirm the typed-record handoffs (not stdout scraping) carry the data.

Anti-Patterns to Reject

See reference.md for the four named anti-patterns and their replacements:

1. Brittle stdout / JSON scraping of agent output → typed, owner-only (0o600), freshness-checked records read fail-CLOSED.
2. Imperative heuristics standing in for judgment (classify_signal, orient, decide) → an agentic step behind a prompt.
3. Wall-clock timeouts that kill working agentic steps → idle/liveness detection.
4. Passing large payloads via argv/env (E2BIG) → route via stdin or a file the tool reads.

Templates & Example

• templates.md — copy-ready recipe, prompt, typed-record, and fail-closed-reader skeletons matching the repo's real shapes.
• worked-example.md — one behavior (classify + route a signal) built as recipe + prompt + typed record + ~10-line rail, contrasted with a naive hardcoded function.

§7 — Honest note on reflexive irony

Some shipped recipes in this repo still hand data between steps by having a later step parse an earlier step's stdout (e.g. parse_json over agent output). That works, and this skill does not claim those recipes are broken. The recipe step is the agentic unit either way. What this skill teaches is the improved handoff: a step writes a typed record (owner-only, freshness-checked) and the next step reads it fail-closed. Model new work on the typed-record handoff; treat stdout-scraping as legacy, not as the target pattern.