FirstPick

Brave Search tool for Pi with API key resolution from env and .env files.

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,

High-fidelity, fail-closed XLSX/XLSM inspection, rendering, editing, diffing, and validation tools for Pi agents.

Safe per-process Natural Conversation Mode for Pi, with /talk commands and read-only tool constraints.

Pi Web UI companion package with a local browser UI CLI plus /webui-start and /webui-status commands.

Memory helper commands and remember_note tool for Pi.

Enhanced Pi footer with git status, token usage, context usage, and model telemetry.

Autonomous PLAN.md execution loop for Pi that continues until all checklist items are complete.

Tech news tools and commands for Pi using Hacker News, Reddit, Socket.dev, and daily.dev sources.

Token and cost usage analytics command for Pi session history.

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 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.

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 when comparing competing products, services, libraries, tools, vendors, or approaches for market/product positioning, feature matrices, strategic trade-offs, pricing, adoption, or differentiation.

Agents should invoke this skill for refactors, code smells, migrations, duplication removal, module splitting, API cleanup, or restructuring plans. Emphasizes small safe steps, behavior preservation, and verification after each change.

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 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 as the final gate before release, handoff, or claiming completion for substantial changes. Runs acceptance/readiness checks, determines pass/fail, and gives a go/no-go recommendation.

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 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 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.

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 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 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 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.

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 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 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 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 when checking CVEs or known vulnerabilities in installed packages, dependencies, Docker images, OS packages, exposed services, or software versions. Produces severity-rated scan reports.

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.

Agents should invoke this skill when defects, regressions, failed tests, unexpected behavior, or spec mismatches are found. Produces structured reproducible bug reports with severity, evidence, environment, and actionable next steps.

Aggressive automatic todo progress widget for multi-goal prompts in Pi.

Self-contained Pi package for skill lifecycle management: memory, skill-bank audit, evaluation, creation, and refinement tools.