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Found 2,164 Skills
Capture and persist lessons learned from a session to compound knowledge over time. Triggers on "/lessons-learned", "what did we learn", "save lessons", "update skills with what we learned", or at the end of a complex multi-session task. PROACTIVE USE: This skill should also be suggested or invoked (1) when resuming from context compaction (the previous context likely contained unrecorded lessons), (2) after resolving a non-trivial bug or debugging session, (3) after significant friction or failed approaches that yielded insight, (4) after a council-of-bots review that surfaced fixes. Identifies reusable patterns, bug fixes, workflow insights, and tool quirks, then persists them to the right places: auto-memory (project-specific), skill files (reusable across projects), or both.
Import/export pipeline for UnoPim. Activates when configuring imports, exports, debugging job pipelines, or creating data transfer profiles; or when the user mentions import, export, CSV, Excel, job, queue, batch, or data transfer.
Full-stack head manager built for Vue. ALWAYS use when writing code importing "@unhead/vue". Consult for debugging, best practices, or modifying @unhead/vue, unhead/vue, unhead vue, unhead.
[Manual Only] Record project learnings in FORyusuke.md. Structurally append lessons learned, pitfalls, debugging stories, and improvement points obtained during the session. It only works when explicitly called via /teach (it will not be triggered automatically in normal work).
AArch64 and ARM assembly skill for reading and writing ARM assembly code. Use when reading GCC/Clang output for AArch64 or ARM Thumb targets, writing inline asm in C/C++, understanding the ARM ABI (AAPCS64/AAPCS), or debugging register and stack state on ARM hardware or QEMU. Activates on queries about AArch64 assembly, ARM Thumb, NEON/SVE SIMD, ARM calling convention, inline asm for ARM, or reading ARM disassembly.
Sentry error tracking and debugging specialist
Configure and collect crash dumps for modern .NET applications. USE FOR: enabling automatic crash dumps for CoreCLR or NativeAOT, capturing dumps from running .NET processes, setting up dump collection in Docker or Kubernetes, using dotnet-dump collect or createdump. DO NOT USE FOR: analyzing or debugging dumps, post-mortem investigation with lldb/windbg/dotnet-dump analyze, profiling or tracing, or for .NET Framework processes.
CrewAI agent design and configuration. Use when creating, configuring, or debugging crewAI agents — choosing role/goal/backstory, selecting LLMs, assigning tools, tuning max_iter/max_rpm/max_execution_time, enabling planning/code execution/delegation, setting up knowledge sources, using guardrails, or configuring agents in YAML vs code.
Browse and recall OpenCode local memory stored on the user's machine: local sessions, plans, conversations, prompt history, and project context. Use immediately when the user asks to check history, previous sessions, past chats, what did we do before, last time, check plans, session history, recall, memory, remember, prior work, previous context, or have we done this before. Auto-trigger proactively when resuming work, continuing a project, referencing prior decisions, debugging repeated issues, revisiting earlier plans, or any follow-up where earlier OpenCode context may help. This means OpenCode local history/files specifically, not ChatGPT/Claude cloud history, generic web search, or unrelated product memory systems. Do NOT use for fresh tasks with no relevant history, or when current files/git already answer the question.
Use when writing, reviewing, or debugging pure Ruby code — idiomatic patterns, modern 3.x+ features (pattern matching, Data.define, endless methods), error handling conventions (raise vs fail, result objects), memoization, and performance idioms. For Rails use rails-guides. For testing use minitest. For code style use sandi-metz-rules.
Execute a lightweight ad-hoc task (debugging, documentation, small adjustments) without the full change lifecycle. Assesses spec impact afterward.
Apply systems thinking — causal loop diagrams, stock-and-flow models, system archetypes, and leverage-point analysis — to organizational, economic, or social problems where feedback loops, delays, or emergent behavior drive recurring failure across multiple interacting actors. Use this skill when the user describes a multi-actor situation that resists linear fixes: policy interventions that backfire, org-level fixes that break other teams, market symptoms that return after being solved, or time-lagged second-order consequences, even if they say 'why does fixing X make Y worse' or 'identify the leverage points in this system'. Do NOT use for single-cause software bugs, flaky tests, or regressions — those are debugging problems, not systems-thinking problems, even when phrased as 'this keeps coming back'.