babysitStage 5 (Deploy) PR shepherding for the AI-native SDLC. Sweep a PR's unresolved review comments and failing checks, address them, push fixes, and repeat until the PR is green and waits only on code owner approval. Use on /sdlc:babysit or when asked to get a PR to green / address review comments.
eval-addStage 4 (Test) continuous evals. Turn a production incident, a fixed bug, or a real recent task into a permanent eval case under evals/cases/ so the agent configuration (CLAUDE.md, skills, hooks, REVIEW.md) is regression-tested in CI. Use on /sdlc:eval-add or when asked to add an eval / regression c
incidentStage 6 (Maintain) of the AI-native SDLC. Diagnose an anomaly, alert, ticket, or channel message with read-only tools, write the finding as an incident intent.md that re-enters the loop, and update lessons.md. Use on /sdlc:incident, when a control band is breached, when asked to investigate an alert
intentStage 1 (Plan) of the AI-native SDLC. Turn an idea, ticket, or problem statement into a committed intent.md through an analyst-style brainstorm. Use when someone has an idea, describes a pain point, wants to "write this up", or says /sdlc:intent. Works for non-engineers.
metricsCompute and explain the AI-native SDLC's leading and lagging indicators from Git history, PR metadata and CI (intent time-to-commit, intent→spec, spec→plan, plan→merge, rework counts, first-pass CI success, review time, gate waits, breach→intent). Use on /sdlc:metrics or when leadership asks how the
planStage 3 (Build) entry of the AI-native SDLC. In plan mode, interview the engineer against an accepted spec.md and produce a committed plan.md (files that change, order of work, risks, options not taken, proof) before any code is written. Use on /sdlc:plan or when asked to plan a change that has a sp
brand-guidelinesThe organisation's brand and content standards applied to specs and UI work. Use when writing spec.md for anything customer- or employee-facing, when producing UI copy, emails, notifications, or visual components, and when reviewing front-end changes.
compliance-policyRegulatory and change-management obligations as constraints on specs, plans, releases and reviews. Use when writing spec.md or plan.md, when a change affects regulated processes, audit trails, records retention, customer communications, or when preparing a release, and during the Compliance review p
secure-api-reviewApply the API security standard. Use whenever creating or modifying an external-facing endpoint, reviewing API code, or generating an OpenAPI spec.
security-policyThe organisation's security policy as constraints on specs, plans, code and reviews. Use when writing spec.md or plan.md, when a change touches authentication, authorisation, secrets, PII or regulated data, network egress, dependencies, or infrastructure, and during the Security review pass.
ux-standardsInteraction, accessibility and content-structure standards for anything users touch. Use when writing spec.md for a user-facing change, designing flows or states, building or reviewing UI, or comparing an implementation to a mock.
releaseStage 5 (Deploy) release of the AI-native SDLC. Prepare a release (changelog from merged changes, checks, staging rehearsal), deploy through tiered environments via MCP or the configured commands, and stop at the production gate until a release manager authorises. Use on /sdlc:release or when asked
reviewStage 5 (Deploy) AI review of the AI-native SDLC. Apply REVIEW.md's passes (bugs, security, compliance against spec.md and plan.md) to a diff, branch or PR, rank findings by severity, cap nits, and emit a machine-readable tally. Use on /sdlc:review, when asked to review a PR/diff/branch, or non-inte
rollbackRoll back an environment to the previous release using the single rehearsed rollback command, then record the incident intent. Use on /sdlc:rollback, when a deploy fails, when a post-deploy control band is breached, or when asked to revert a release.
sdlc-loopShared reference for the AI-native SDLC loop used by every /sdlc command. Load when working with intent.md, spec.md, plan.md, sdlc/changes, sdlc/incidents, REVIEW.md, release gates, or sdlc.config.json, or when asked how the SDLC loop, its artifacts, gates or roles work.
setupInstall the AI-native SDLC loop into a product repository. Asks about CI platform (GitHub/GitLab/both), tracker, chat, monitoring, build/test/lint commands and protected paths, then scaffolds sdlc/, sdlc.config.json, REVIEW.md, CI workflows, evals, monitoring, MCP connectors and the CLAUDE.md sectio
specStage 2 (Design) of the AI-native SDLC. Read an accepted intent.md and produce a requirements-and-design spec.md constrained by the organisation's policy skills (security, compliance, brand, UX), with flagged concerns first. Use when an intent is accepted, when asked for a spec/requirements/design f
statusShow where every change and incident is in the AI-native SDLC loop (which artifact exists, its status, who owns the next gate), plus open PRs linked to changes. Use on /sdlc:status or when asked "where is change X", "what is waiting on me", or for a loop overview.
tracker-syncKeep the legacy tracker (Jira, YouTrack, GitLab issues, GitHub issues) and the Markdown artifacts linked according to sdlc.config.json sourceOfTruth (repo | tracker | linked). Read the record at session start, write outcomes and commit SHAs back through the tracker's MCP connector. Load whenever an
verifyStage 4 (Test) of the AI-native SDLC. Give Claude a way to check its own work: run the configured build/test/lint with quantifiable targets, drive the failing-test-first bug-fix flow (with the test-file lock), and the screenshot loop for UI. Use on /sdlc:verify, when asked to verify/prove a change w