Agents should invoke this skill for code security reviews, leaked secret checks, dependency risk, unsafe shell/Python/TypeScript/Rust patterns, auth/input-validation flaws, SAST-style audits, or supply-chain concerns in repositories.
Pi command to run npm package release workflow with publish confirmation.
Agents should invoke this skill for Linux server security reviews, SSH hardening, firewall/open-port audits, user/permission checks, exposed services, or host hardening requests. Produces severity-rated findings and practical remediation steps.
Agents should invoke this skill before modifying unfamiliar codebases, answering where/how something is implemented, tracing dependencies, mapping repo structure, or planning changes. Explores a repository and returns a strict JSON handoff with key files,
Self-contained Pi package for skill lifecycle management: memory, skill-bank audit, evaluation, creation, and refinement tools.
Agents should invoke this skill for high-stakes or complex research needing multi-source evidence, scientific/technical fact-checking, decision traces, or rigorous verification. Runs deterministic two-phase research with schema/policy validation.
Agents should invoke this skill for backup health checks, restore testing, NAS/Gitea backup integrity, 3-2-1 strategy review, backup script audits, or verifying repositories and archives can be restored safely.
Agents should invoke this skill for academic or technical papers, arXiv/PubMed/IEEE/ACM links, PDFs, methodology review, limitations, practical implications, or extracting findings for engineering decisions.
Agents should invoke this skill for code reviews, linting/formatting setup, maintainability checks, complexity concerns, warning cleanup, coding standards, or quality gates in Rust, TypeScript, Python, shell, and mixed repos.
Agents should invoke this skill when planning tests from specs, architecture docs, PRs, risky changes, new features, bug fixes, or release work. Generates prioritized unit, integration, E2E, regression, and edge-case coverage.
Agents should invoke this skill for connectivity, DNS, Pi-hole, port reachability, routing, firewall reachability, TLS/network timeouts, or service access failures. Provides structured network troubleshooting commands and interpretation.
Agents should invoke this skill for Docker Compose deployments, container updates, stack health checks, rollbacks, compose-file changes, image upgrades, failed deploys, or service restart planning. Provides safe deployment and rollback workflows.
Agents should invoke this skill for slow code, high CPU/memory, latency, large data processing, algorithmic complexity, profiling plans, benchmarks, or optimization requests. Profiles first and weighs trade-offs before changing code.
Agents should invoke this skill when checking CVEs or known vulnerabilities in installed packages, dependencies, Docker images, OS packages, exposed services, or software versions. Produces severity-rated scan reports.
Linter for agent skill files
Agents should invoke this skill for broad multi-claim research projects needing planning, parallel investigation, source merging, gap closure, citation audit, and final synthesis when narrower research skills are insufficient.
Upgrade npm-installed Pi extensions with up-to-date checks.
Agents should invoke this skill when identifying, categorizing, prioritizing, or planning technical debt work, debt sprints, cleanup backlogs, TODO consolidation, or long-term maintainability risks. Tracks debt with severity/effort.
Pi package with skill invocation and visibility improvements.
Agents should invoke this skill for architecture reviews, module boundaries, dependency direction, coupling/cohesion, SOLID concerns, system design trade-offs, layering, service boundaries, or design decisions before implementation.
Agents should invoke this skill when choosing or evaluating libraries, frameworks, tools, platforms, models, databases, APIs, or architectures for a use case. Produces criteria scoring, ecosystem assessment, and recommendations.
Agents should invoke this skill for Tauri + Django + React desktop apps, especially backend lifecycle, CORS/auth, frontend integration, build packaging, dual desktop/web deployment, Rust commands, and platform-specific gotchas.
Agents should invoke this skill when choosing patterns, designing traits/interfaces/components, deciding abstraction boundaries, evaluating dependency injection/callbacks, or comparing implementation approaches in Rust, TypeScript/React, or Django/Python.
Agents should invoke this skill when a spec, plan, README, issue, or requirement must be verified against implementation. Traces requirements to code, checks interface contracts, and reports gaps or mismatches.