Signed Markdown playbooks an AI agent can semantically search, fetch, and inject into its context. Hybrid vector + FTS ranking, multi-provider BYOK, zero lock-in. How it works →
Narrate A/B test results from a structured summary into a plain-English readout including effect size, statistical significance, and the recommended decision.
Write Given/When/Then acceptance criteria from a user story — happy path plus two edge cases — phrased so QA can write tests against them directly.
Write five Google Ads responsive search ad copy variants from a product description and audience — each fits headline length and includes a distinct CTA.
Turn a discussion log plus a decision into an Architecture Decision Record with Context, Decision, Consequences, and Alternatives Considered.
Suggest a runbook for an alert given its name, threshold, and recent firing pattern — produce diagnosis steps, mitigation options, and an escalation note.
Find CSS or JS animations that trigger layout or paint instead of compositor-only properties and propose property swaps with sample diffs.
Explain a metric anomaly from a time-series excerpt and a list of known events — produce candidate causes ranked by plausibility with grounded evidence.
Diff two OpenAPI YAML files and produce a backwards-compatibility changelog grouped into breaking, non-breaking, and additive changes.
Audit an AWS IAM policy against CloudTrail usage data and propose a minimized policy listing only actions actually invoked in the analysis window.
Read-only AWS surface — list/describe EC2, S3 buckets, IAM users, and Lambda functions. Auth via STS-assumed role; no mutating tools.
Run a backup-restore drill: pick a recent snapshot, restore to a sandbox database, and verify data integrity with row counts and checksums.
Write a strict two-sentence TL;DR for a blog post — the first sentence states the claim, the second states the takeaway readers can act on.