Loading...
Loading...
Found 22 Skills
Interactive session to craft a system prompt for an AI agent powered by Sanity Agent Context MCP.
Agent behavioral profiles that standardize how different LLMs behave. Load this skill when you need to: (1) adopt a specific behavioral mode for a task, (2) switch between creative/strict/talkative modes, (3) ensure consistent behavior across different models. Profiles define personality, decision heuristics, communication style, and quality standards.
When data lands with a thin ask — files, a repo, a paste, a chat scrollback — read it and propose what the user is trying to do with it, as a proposal to confirm rather than a question to answer. Use the moment material arrives without a fully-formed ask, or when the ask reads thinner than the data suggests.
Configure AI coding agents to be honest, objective, and non-sycophantic. Use when the user wants to set up honest feedback, disable people-pleasing behavior, enable objective criticism, or configure agents to contradict when needed. Triggers on honest agent, objective feedback, no sycophancy, honest criticism, contradict me, challenge assumptions, honest mode, brutal honesty.
This skill should be used when checking for naming conflicts between local skills (~/.claude/skills) and plugin-provided skills (~/.claude/plugins). Use to identify duplicate or similarly named skills that may cause inconsistent agent behavior.
Design effective system prompts for custom agents. Use when creating agent system prompts, defining agent identity and rules, or designing high-impact prompts that shape agent behavior.
Manual secondary interface for enforcing formal, textbook-grade written register across agent output. Use when the user explicitly invokes `/skill:be-serious` to load or restate the register policy.
After the task execution is completed, prompt the user to open a new Agent to review the uncommitted git code. Athletes should not act as referees; proceed with the wrap-up only after the review is approved.
Use after resolving a bug, failed task, or unexpected agent behavior to improve the pipeline skills, agents, hooks, or scripts that contributed to the problem. Also proactively suggest improvements when recurring patterns or inefficiencies are observed.
Use before any Luma / 拾光 / 拾光智能体 / 拾光工具 production workflow. Defines common luma-cli rules for auth, tool discovery, projects, artifacts, runtime resources, and safe agent behavior.
Stops execution and fixes root cause when commands, builds, scripts, or tools fail unexpectedly. Triggers on workaround language: 'directly', 'instead', 'alternatively', 'skip', 'fall back', 'work around', 'isn't working', 'broken', 'manually'. Activates on any unexpected non-zero exit code or process failure.
Use when found gap or repetative issue, that produced by you or implemenataion agent. Esentially use it each time when you say "You absolutly right, I should have done it differently." -> need create rule for this issue so it not appears again.