48,111 mods in this category, of every kind an
agent can take. Each one carries what it costs per session, what the
scan found, and whether it is the original.
Spec-driven development methodology for Claude Code. Provides skills for requirements engineering (EARS format), design documentation, task breakdown, AI prompting strategies, quality assurance, and troubleshooting.
★not rated 746▲
+3 7mo agoA
tokens not measured
originalMIT
Analyze business requirements against codebase context at a strategic level, producing enriched context (business + domain concepts + strategic direction + risks) for REASONS Canvas generation.
Repo-local workflow skill for large coding tasks. Initializes .agent/tasks/TASKID artifacts, installs project-scoped Codex and Claude subagents, updates AGENTS.md plus the repo's Claude guide file with the workflow, and runs a spec-freeze → build → evidence → verify → fix loop with fresh-session verification.
A structured hiring-assessment workflow that turns a candidate's résumé and a job description into reviewable evidence, interview questions, and an offline HTML report for interviewers.
Evidence-first development — surround the implementation with an executable spec and a gauntlet of constraints (tests, types, coverage, mutation) so line-by-line review becomes optional. Use when the user explicitly asks for high-assurance or evidence-first work ("reliable", "TDD", "prove it works", "I won't read the…
Orchestrator reference for pi-messenger Crew planning, task management, configuration, and agent coordination. Crew workers already have the pimessenger actions they need in crew-worker.md.
Systems architect specializing in the design, coordination, and governance of multi-agent AI pipelines — covering topology selection, context management, inter-agent trust, failure recovery, human-in-the-loop gating, and observability for production-grade agent systems.
End-of-turn research process recorder with progressive crystallization. Invoked at the END of EVERY turn, after the user's current request has been fully addressed and before yielding control back to the user. Reviews what happened in the turn, extracts research-significant events, and writes them into the ara/…
Interactive planning agent - clarifies WHAT to build and figures out HOW. Lightweight requirements engineering, approach exploration, design validation, premortem, plan + todos. Can spawn scouts/researchers mid-session when it needs facts.
Plan and autonomously build a software task end-to-end. Recons the codebase, applies preloaded memory, decomposes into the right number of phases, gets one confirmation, then prepares a single ready-to-paste /goal command — one paste between you and done — that drives execution to completion with built-in retry…
★not rated 670▲
+3 18d agoA
tokens not measured
originalMIT
Enter "plan mode" for a coding task — read the relevant code, optionally ask clarifying questions, design one recommended approach, then write a plain, scannable plans/ - .md file. No source files are edited in this mode. Use this skill whenever the user says "plan mode", "/coding-plan", "make a plan", "draft a plan…
Plans trips with points, miles, awards, and cash. Use for any travel research, flight comparison, hotel booking, points balance check, or trip planning request.
A Chinese-language research and planning tool for mapping where a company could use artificial intelligence. It researches the company and industry, then organizes possible uses, priorities, and an implementation path.
Claude Code instructions for henrydaum/second-brain, covering second brain — architecture notes, ⚡ the kernel (read first), the layout (trees.py), what ships in the app's tree (bundled/) and the kernel boundary (the one rule).
Instructions for Decade-qiu/CookHero, covering global instructions, 0. general code quality requirements, 1. task decomposition & planning, 2. version compatibility policy and 3. git operations.
Acceptance test creation methodology for the DISTILL wave. Domain knowledge for the acceptance designer agent: port-to-port principle, prior wave reading, wave-decision reconciliation, graceful degradation, and document back-propagation.
★not rated 605▲
+3 todayA46 tokens
originalMIT
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