Red-team a product, architecture, implementation, migration, or launch plan before execution. Use for pre-mortems, strategy or scope challenge, and independent testing of assumptions, dependencies, and failure modes — not code.
Critique customer interface flows using interaction, visual, responsive, keyboard and screen-reader accessibility, content, and runtime evidence. Use for UX audits, design reviews, UI polish, onboarding, empty states, or redesign.
Discovery, specification, launch, and learning for a product in one loop. Build-or-stop calls, MVP wedges, demand tests, customer interviews, PRDs, requirements, user journeys, acceptance, positioning, onboarding, rollout, pricing, pivots.
Audit production operability and operational fitness: go/no-go, rollback, migrations, observability, recovery, support and halt thresholds; separate local, exact-head CI, runtime, deployed, and public release proof.
Select and generate the correct LICENSE — MIT for public fmind/fmind-ai repos, otherwise proprietary — and update project manifests. Use when adding or fixing a project's license.
Design production LLM or agent prompt stacks: instructions, tool contracts, examples, outputs, and runtime context. Use for precedence, conflicts, dynamic or untrusted context; prove behavior with agent-evaluation.
Write standalone single-file Python scripts using PEP 723 inline metadata and uv. Use when creating a quick CLI script that needs dependencies without a full project.
Design and execute risk-based test campaigns and exercise risky feature journeys; identify what remains unproved across unit, integration, E2E, browser, accessibility, performance, resilience, and manual tests. Not a diff review.
Sync AGENTS.md (for agents) and README.md (for humans) with the codebase's current tools, layout, and usage. Use when either drifts from the project's actual state.
Cut or verify a versioned release — bump semver, generate the changelog with git-cliff, tag and publish on GitHub, or reconcile an already-published tag and assets.
Reconstruct why tracked code exists from read-only Git history. Trace files, symbols, or lines through introducing commits or pull requests, rationale, reverts, renames, authorship, co-change clues, and issues.
Audit a whole repository across architecture, source, tests, tooling, security, CI/CD, docs, and releases. Use for cross-cutting audits, readiness, or technical-debt reviews with ranked findings — not one diff or release candidate.
Audit third-party Agent Skills/extensions for supply-chain security without running them before install/trust. Inspect scripts, hooks, MCP/plugins, hidden instructions, symlinks, credential/network flows, and provenance/licenses.
Diagnose unknown-cause bugs, test/build or auth failures, flakes, and runtime performance regressions. Investigate, reduce, localize, falsify hypotheses, and explain root cause before implementation.
Publish source-grounded technical articles across draft, canonical site, export, and public verification. Not software releases or standalone documents.
Verify unfamiliar framework APIs and architectures from exact local dependency source and current primary docs. Compare installed packages, specs, and versions before choosing an approach; return a recommendation with proof boundaries.
Canonical infrastructure-as-code stack — OpenTofu-first with tflint, trivy config scans, terraform-docs, native tests, and GCS state. Use for any Terraform or OpenTofu work.
Implement an isolated bug fix or behavior change with an honest red-green-refactor cycle. Use when a regression test should fail before the correction, or when tested logic, refactors, or seams must prove correctness.