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Agentic Workflows

Repo-native operating files for controlled AI work.

Prompts are not the product. The product is the operating loop: context, delegation, verification, approval, artifact, learning.

What this is

agentic-workflows turns AI workflows into repo-native operating files: validate them, render runbooks, audit authority, and compile them into agent skills.

It is still a playbook, but v2 adds a runnable foundation:

  • .workflow.yml files for executable-style workflow definitions
  • a machine-readable workflow schema
  • a Bun CLI for validation, runbook rendering, authority audit, and scaffolding
  • repo templates for AGENTS.md and skill drafts

The emphasis is not on clever phrasing. The emphasis is on the operating system around the agent:

  • what context the agent receives
  • what authority it has
  • how work is delegated
  • what must be verified
  • which actions require human approval
  • what artifact is produced
  • what lesson is saved for next time

This is not a prompt dump. Each workflow includes:

  • when to use it
  • required context
  • authority boundaries
  • expected artifact
  • verification gate
  • failure modes
  • public-safe synthetic examples

Quick start

Requirements:

Run the CLI from the repo root:

bun run validate
bun cli/aw.ts check
bun cli/aw.ts check-skills
bun cli/aw.ts publication-scan
bun cli/aw.ts publication-scan --list
bun cli/aw.ts runbook workflows/repo-triage.workflow.yml
bun cli/aw.ts audit workflows/research-to-decision.workflow.yml
bun cli/aw.ts new workflow customer-feedback-triage
bun cli/aw.ts new skill launch-readiness

CLI commands:

aw validate <workflow>
aw check [workflow...]
aw check-skills [skill...]
aw publication-scan [--list] [file...]
aw runbook <workflow>
aw audit <workflow>
aw new workflow <name>
aw new skill <name>

Who this is for

  • founders, operators, chiefs of staff, and product leads adopting AI agents
  • engineering and product teams designing human-in-the-loop workflows
  • people evaluating what competent AI delegation looks like in practice
  • anyone who wants less AI theater and more reliable AI-assisted execution

The operating loop

flowchart LR
  A[Context] --> B[Delegation]
  B --> C[Execution]
  C --> D[Verification]
  D --> E{Approval needed?}
  E -- No --> F[Artifact]
  E -- Yes --> G[Human approval]
  G --> F
  F --> H[Learning]
  H --> A
Loading

A good agentic workflow is a loop, not a one-off prompt. It starts with scoped context, delegates work with clear authority, verifies the result, gates risky actions, produces an artifact, and captures reusable lessons.

Core principles

  1. Artifacts over prompts — a workflow should end in something durable: a memo, PR, issue tree, checklist, test result, decision log, or report.
  2. Human-controlled authority — AI may draft, inspect, summarize, and propose; humans approve external writes, destructive actions, and sensitive decisions.
  3. Main-agent accountability — parallel agents can help, but the operator synthesizes, verifies, and owns the recommendation.
  4. Private by default — workflows are templates. Examples are synthetic. Private memory, secrets, client work, and internal context do not belong here.
  5. Learning compounds — save reusable procedures and failure modes, not raw transcripts.

Executable workflow files

Executable-style examples live beside the markdown playbooks:

Workflow file Use it for Try it
repo-triage.workflow.yml Mapping an unfamiliar repo before edits bun cli/aw.ts runbook workflows/repo-triage.workflow.yml
research-to-decision.workflow.yml Research that must end in a recommendation bun cli/aw.ts audit workflows/research-to-decision.workflow.yml
external-action-gate.workflow.yml Preparing an external write for approval bun cli/aw.ts runbook workflows/external-action-gate.workflow.yml
analytics-consent-audit.workflow.yml Auditing consent-gated analytics and conversion tracking bun cli/aw.ts runbook workflows/analytics-consent-audit.workflow.yml
google-ads-upload-qa.workflow.yml Reviewing Google Ads bulk uploads before posting account changes bun cli/aw.ts audit workflows/google-ads-upload-qa.workflow.yml
ad-preflight-review.workflow.yml Reviewing ad copy, claims, landing-page alignment, and launch approvals bun cli/aw.ts audit workflows/ad-preflight-review.workflow.yml
paid-social-launch-gate.workflow.yml Gating paid-social submission, enablement, event changes, and spend scaling bun cli/aw.ts audit workflows/paid-social-launch-gate.workflow.yml
technical-seo-launch-audit.workflow.yml Auditing crawl, indexation, metadata, sitemap, robots, and schema launch readiness bun cli/aw.ts runbook workflows/technical-seo-launch-audit.workflow.yml
product-marketing-context-builder.workflow.yml Building stable product, audience, proof, and claim-boundary context bun cli/aw.ts runbook workflows/product-marketing-context-builder.workflow.yml
growth-loop-diagnosis.workflow.yml Diagnosing growth loops, weak links, confidence, and next experiments bun cli/aw.ts audit workflows/growth-loop-diagnosis.workflow.yml
social-content-fact-check-rewrite.workflow.yml Reviewing and rewriting social posts before publication bun cli/aw.ts audit workflows/social-content-fact-check-rewrite.workflow.yml
growth-launch-readiness.workflow.yml Chaining context, creative, launch, analytics, approval, and learning checks bun cli/aw.ts runbook workflows/growth-launch-readiness.workflow.yml

The schema is schema/workflow.schema.json.

Each workflow declares:

  • name
  • goal
  • trigger
  • inputs
  • allowed_tools
  • authority
  • risk_level
  • required_permissions
  • external_side_effects
  • destructive_actions
  • dry_run
  • approval_required
  • steps
  • verification
  • artifacts
  • memory_update

Growth marketing skills

The skills/ directory contains repo-native skill drafts for repeatable growth marketing workflows. These skills are public-safe operating files, not private prompt dumps. Each skill names its inputs, authority boundary, approval gates, verification gate, and output artifact. check-skills also rejects a small set of obvious publication-policy violations such as private home paths and common token shapes.

Current skills:

Skill Use it for
analytics-consent-audit Auditing consent state, tag loading, conversion-event dispatch, and attribution evidence
google-ads-upload-qa Reviewing Google Ads bulk upload packages before posting account changes
ad-preflight-review Reviewing ad copy, claims, landing-page alignment, and approval requirements before launch
paid-social-launch-gate Verifying paid-social launch readiness before submission, enablement, or scaling
technical-seo-launch-audit Checking crawl, indexation, metadata, sitemap, robots, and schema launch readiness
product-marketing-context-builder Building stable product, audience, proof, and claim-boundary context for growth work
growth-loop-diagnosis Diagnosing the current growth loop, weakest link, confidence, and next experiment
social-content-fact-check-rewrite Fact-checking and rewriting social posts before publication

Use growth skill eval prompts to test each skill with synthetic Acme Sleep scenarios and a shared scoring rubric.

Validate skills and public-facing files with:

bun cli/aw.ts check-skills
bun cli/aw.ts publication-scan
bun cli/aw.ts publication-scan --list

Authority levels

Level Meaning
read_only Inspect, summarize, and recommend. Do not modify files or external systems.
local_write Modify files in the local repo or workspace. Do not write to external systems.
external_draft Draft external-facing messages, issues, posts, or PR text. Do not send or publish.
external_write_requires_approval Prepare an external write, then stop for explicit human approval before execution.
destructive_forbidden Destructive actions are outside scope, even with tool access.

Markdown playbooks

Workflow Use it for Output artifact
Agentic project pulse Project health and next actions Pulse memo
Approval boundary matrix Defining what agents may do Authority table
Subagent delegation brief Parallel task delegation Brief + result spec
Multi-agent review loop Research/review/design sprints Synthesized recommendation
External action gate Sending/posting/commenting/publishing Approval checklist
Analytics consent audit Checking consent-gated analytics and conversion tracking Audit report
Google Ads upload QA Reviewing paid-search bulk uploads before account changes QA report
Ad preflight review Reviewing ad claims, landing-page alignment, and launch approvals Preflight report
Paid social launch gate Checking paid-social launch readiness before platform-visible changes Launch gate report
Technical SEO launch audit Checking crawl, indexation, sitemap, robots, metadata, and schema readiness SEO audit report
Product marketing context builder Building reusable product, audience, proof, and claim-boundary context Context document
Growth loop diagnosis Diagnosing growth loops and selecting the next experiment Decision memo
Social content fact-check rewrite Reviewing and rewriting social content before publication Claim table + draft
Growth launch readiness Chaining context, creative, launch, analytics, approval, and learning checks Launch packet
Learning extractor Turning hard-won fixes into reusable knowledge Lesson or skill proposal
Research-to-decision pipeline Research that must become a decision Decision memo
Repo triage workflow Auditing unfamiliar codebases Triage report

Why this is different

Most public AI repositories show prompts, vendor skills, or tool recipes. This repo shows the operating layer around AI work: delegation contracts, approval gates, verification standards, learning loops, and measurable artifacts.

The goal is to make AI work safer and more legible, especially when agents touch real projects, code, tasks, or external systems.

Safety posture

All examples are synthetic. Do not commit secrets, private conversations, client/employer material, real account IDs, internal repo names, or hidden system prompts. See Publication policy.

Repository layout

cli/         Bun CLI for workflow validation, runbooks, audits, and scaffolds
principles/   Core operating beliefs
schema/      Machine-readable workflow schema
skills/      Public-safe skill drafts for repeatable AI-assisted work
workflows/   Reusable playbooks and executable-style workflow files
templates/   Copy/paste templates, AGENTS.md template, skill draft template
examples/     Synthetic case studies and eval prompts
diagrams/     Visual explanations

Contributing

Contributions should improve public-safe workflows, templates, examples, or safety practices. See Contributing.

License

CC BY 4.0. See License.

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