Turn accepted requirements into ordered dependency-aware slices and a repository-grounded implementation plan. Use before editing when work spans systems, has migration or rollout risk, needs architecture choices, or should be split.
Create and manage local Kubernetes clusters (k3d or kind) and deploy to them with kubectl, helm, helmfile, and skaffold. Use for local k8s cluster setup, dev loops, and debugging.
Canonical lefthook git-hooks setup — pre-commit (format, check, secret scan) and pre-push (test), each delegating to mise run tasks. Use when configuring or debugging git hooks.
Create, theme, validate, and embed Mermaid diagrams as the default text-based diagram format for GitHub, Slidev, documentation, and technical communication.
Execute an accepted implementation plan in bounded, verified slices. Use to coordinate multiple agents and shared-file ownership, resume planned work, or finish scoped tasks without crossing commit, push, deploy, or publication boundaries.
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.
Manage secrets with sops and age: commit encrypted files, decrypt only in memory, and wire Flux or OpenTofu runtimes.
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originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: