Agentic Workflow Reliability Audit

Agentic Workflow Reliability Audit is a small public proof surface for teams experimenting with AI agents, coding workers, schedulers, or LLM automations.

It shows a practical, evidence-first way to inspect agent workflows for repeated work, missed state, unsafe side effects, weak review gates, and missing evidence trails. The material here is synthetic examples only: static files, no accounts, no runtime service, no tracking, no paid offer, and no data intake.

What is included

• checklists/reliability-audit-checklist.md — a source-grounded checklist for reviewing an agent workflow.
• examples/synthetic-audit-report.md — a synthetic example report for a fictional internal automation.
• examples/evidence-bundle-template.md — a compact template for proving what changed and what was verified.
• docs/index.html — a static no-data/no-payment landing page.
• scripts/validate_public_package.py — a local validator for public-copy boundaries.

Boundaries

• Synthetic examples only.
• No real customer, company, user, or product data.
• No payment, invoice, refund, support, or money flow.
• No forms, uploads, tracking, cookies, storage, analytics, or runtime network calls.
• Not legal, tax, compliance, procurement, security, certification, or regulatory advice.
• No guaranteed outcomes.
• No claim that this audit makes an AI system safe, secure, compliant, profitable, production-ready, or fully autonomous.
• A passing validator is only a local copy-safety signal; it is not approval to publish, send, certify, sell, or claim anything.

Public fit-check

If this checklist is useful, open a GitHub issue with a public/non-sensitive workflow failure pattern or suggestion.

Do not include confidential, client, customer, product, security, accounting, tender, procurement, contractual, legal, internal business, personal, secret, credential, token, log, private URL, screenshot, attachment, account identifier, or other sensitive content.

This repository does not accept paid work, payment, support requests, statements of work, contracts, invoices, procurement requests, service commitments, legal advice, security review, compliance certification, or guaranteed outcomes through GitHub Issues. Any private or commercial work would require a separate private approval, payment, and legal boundary outside this repository.

Run locally

python3 scripts/validate_public_package.py
python3 -m unittest discover -s tests -v

Validation question

Can a narrow, evidence-backed, no-claims public proof surface attract useful signal from builders who need agent workflow reliability checks, without pretending to be a compliance product or paid service?

Useful external signals would be stars, forks, issues, pull requests, clone/view traffic, or concrete suggestions about the checklist/report format.

There is no paid pilot, lead form, money flow, or service promise here.