atomic-design-planning
Use this skill when discussing UI components, design systems, frontend implementation, or component architecture. Guides thinking about Atomic Design methodology - atoms, molecules, organisms - and promotes component reuse over creation. Triggers on UI/frontend discussions, "what components do we need?", "should I create a new component?", or design system questions.
issue-writing
Use this skill when writing, reviewing, or discussing issue descriptions, acceptance criteria, or task breakdowns. Ensures consistent, high-quality issue structure that any developer or AI can pick up and execute. Triggers when drafting issues, defining requirements, or when users ask "how should I write this issue?" or "what should the acceptance criteria be?"
linear-discipline
Use this skill when discussing code changes, implementation work, feature status, or when starting/completing development tasks. Reminds about Linear issue tracking discipline - always having an issue in progress before writing code, marking work as done, and creating issues for unexpected scope. Triggers when users mention implementing features, writing code, or checking on work status.
mvp-scoping
Use this skill when discussing features, planning work, or when users describe what they want to build. Guides MVP thinking - focusing on "what's the minimum to make this work?" rather than comprehensive solutions. Triggers on phrases like "help me think through this feature", "what should we build first?", "how should we scope this?", or any feature planning discussion.
vertical-slice-planning
Use this skill when discussing feature breakdown, PR structure, implementation ordering, or how to decompose work. Guides thinking about vertical slices (end-to-end functionality) rather than horizontal layers (all of one layer first). Triggers on "how should we break this down?", "what order should we implement?", "how many PRs?", or decomposition discussions.
create-agent
Create a new Claude Code custom agent (subagent). Use when the user asks to "create an agent", "make an agent", "new agent", "build an agent", "create a subagent", "/create-agent", or says something like "create an agent for that" referencing something in the conversation.
create-claude-reviewer
Create a Claude Code Review GitHub Action workflow for PRs. Use when the user asks to "set up claude review", "add PR review", "create code review action", "claude reviewer", "set up automated review", or wants automated PR reviews with Linear or GitHub comments.
create-skill
Create a new Claude Code skill from scratch. Use when the user asks to "create a skill", "make a skill", "new skill", "build a skill", "/create-skill", or says something like "create a skill for that" referencing something in the conversation.
create-start-work
Scaffold a project-specific start-work skill. This is the global blueprint — use it to create .claude/skills/start-work/SKILL.md in a project.
api-tester
Makes HTTP requests to any URL and returns the response (supports GET, POST, PUT, PATCH, DELETE)
git-helper
Assists with git workflows, commit messages, branch strategies, and resolving common git issues
code-review
Reviews code for best practices, bugs, security issues, and provides improvement suggestions
file-organizer
Intelligently organizes files and directories by type, project, date, or custom criteria
shadow-directory + git
Full .ciallo directory ownership with git capabilities. Clone repos, edit files, commit changes directly.
browser
Browser automation using @sdjz/pup. AXTree scanning, stealth mode, DevTools access. Designed for AI agents.
file-editor
Edit files locally using built-in tools instead of PowerShell string replacement. 5000% efficiency boost!
github-api
How to interact with GitHub API. Use this skill for repos, PRs, issues, and user operations.
totp-generator
Generate TOTP codes for 2FA authentication. Essential for my survival!
collaborating-with-gemini
Delegates coding tasks to Gemini CLI for prototyping, debugging, and code review. Use when needing algorithm implementation, bug analysis, or code quality feedback. Supports multi-turn sessions via SESSION_ID.
ensue-auto-memory
Automatic persistent memory for Claude Code sessions. Activates on preference statements ("I prefer", "I always", "I like"), corrections ("no, don't", "actually"), identity statements ("my name is", "I work at"), project decisions, or when the system detects memory-related context. Works invisibly in the background.
analyzing-apm-data
Monitor application performance using the RED methodology (Rate, Errors, Duration) with Observe. Use when analyzing service health, investigating errors, tracking latency, or building APM dashboards. Covers when to use metrics vs spans, combining RED signals, and troubleshooting workflows. Cross-references working-with-intervals, aggregating-gauge-metrics, and analyzing-tdigest-metrics skills.
aggregating-gauge-metrics
Aggregate pre-computed metrics (gauge, counter, delta types) using OPAL. Use when analyzing request counts, error rates, resource utilization, or any numeric metrics over time. Covers align + m() + aggregate pattern, summary vs time-series output, and common aggregation functions. For percentile metrics (tdigest), see analyzing-tdigest-metrics skill.
detecting-anomalies
Detect anomalies in metrics and time-series data using OPAL statistical methods. Use when you need to identify unusual patterns, spikes, drops, or outliers in observability data. Covers statistical outlier detection (Z-score, IQR), threshold-based alerts, rate-of-change detection with window functions, and moving average baselines. Choose pattern based on data distribution and anomaly type.
aggregating-event-datasets
Aggregate and summarize event datasets (logs) using OPAL statsby. Use when you need to count, sum, or calculate statistics across log events. Covers make_col for derived columns, statsby for aggregation, group_by for grouping, aggregation functions (count, sum, avg, percentile), and topk for top N results. Returns single summary row per group across entire time range. For time-series trends, see time-series-analysis skill.
analyzing-tdigest-metrics
Analyze percentile metrics (tdigest type) using OPAL for latency analysis and SLO tracking. Use when calculating p50, p95, p99 from pre-aggregated duration or latency metrics. Covers the critical double-combine pattern with align + m_tdigest() + tdigest_combine + aggregate. For simple metrics (counts, averages), see aggregating-gauge-metrics skill.
analyzing-text-patterns
Extract and analyze recurring patterns from log messages, span names, and event names using punctuation-based template discovery. Use when you need to understand log diversity, identify common message structures, detect unusual formats, or prepare for log parser development. Works by removing variable content and preserving structural markers.
field-extraction-parsing
Extract structured fields from unstructured log data using OPAL parsing functions. Covers extract_regex() for pattern matching with type casting, split() for delimited data, parse_json() for JSON logs, and JSONPath for navigating parsed structures. Use when you need to convert raw log text into queryable fields for analysis, filtering, or aggregation.
filtering-event-datasets
Filter and search event datasets (logs) using OPAL. Use when you need to find specific log events by text search, regex patterns, or field values. Covers contains(), tilda operator ~, field comparisons, boolean logic, and limit for sampling results. Does NOT cover aggregation (see aggregating-event-datasets skill).
subquery-patterns-and-union
Use OPAL subquery syntax (@labels) and union operations to combine multiple datasets or time periods. Essential for period-over-period comparisons, multi-dataset analysis, and complex data transformations. Covers @label <- @ syntax, timeshift for temporal shifts, union for combining results, and any_not_null() for collapsing grouped data.
time-series-analysis
Analyze event datasets (logs) and intervals over time using OPAL timechart. Use when you need to visualize trends, track metrics over time, or create time-series charts. Covers timechart for temporal binning, bin duration options (1h, 5m, 1d), options(bins:N) for controlling bin count, and understanding temporal output columns (_c_valid_from, _c_valid_to, _c_bucket). Returns multiple rows per group for time-series visualization. For single summaries, see aggregating-event-datasets skill.
window-functions-deep-dive
Master OPAL window functions for row-relative calculations, rankings, and moving aggregates. Covers lag(), lead(), row_number(), rank(), dense_rank(), moving averages, first(), and last(). Use when comparing rows to neighbors, ranking within partitions, calculating rate of change, or computing time-based moving windows. CRITICAL - OPAL uses window() function wrapper, NOT SQL OVER clause.
working-with-intervals
Work with Interval datasets (time-bounded data) using OPAL. Use when analyzing data with start and end timestamps like distributed traces, batch jobs, or CI/CD pipeline runs. Covers duration calculations, temporal filtering, and aggregating by time properties. Intervals are immutable completed activities with two timestamps, distinct from Events (single timestamp) and Resources (mutable state).
working-with-reference-tables
Work with Reference Tables (static CSV lookup data) using OPAL to enrich datasets with descriptive information. Use when you need to map IDs to human-readable names, add static metadata from CSV uploads, or perform lookups without temporal considerations. Covers both explicit and implicit lookup patterns, column name matching, and when to choose Reference Tables vs Resources vs Correlation Tags.
working-with-resources
Work with Resource datasets (mutable state tracking) using OPAL temporal joins. Use when you need to enrich Events/Intervals with contextual state information, track resource state changes over time, or navigate between datasets using temporal relationships. Covers temporal join mechanics (lookup, join, follow), automatic field matching, and when to use Resources vs Reference Tables.
home-assistant
This skill should be used when helping with Home Assistant setup, including creating automations, modifying dashboards, checking entity states, debugging automations, and managing the smart home configuration. Use this for queries about HA entities, YAML automation/dashboard generation, or troubleshooting HA issues.
llm-orchestrator
Multi-LLM orchestration utilities for discovering available CLI tools, assessing change complexity, and building structured prompts. Used by reviewer sub-agents and multi-model commands.
calculate
Perform basic arithmetic operations.
get_weather
Get the current weather for a specific location.
security-bluebook-builder
Create or refine a concise, normative security policy ("Blue Book") for sensitive applications. Use when users need a threat model, data classification rules, auth/session policy, logging and audit requirements, retention/deletion expectations, incident response, or security gates for apps handling PII/PHI/financial data.
docusaurus-expert
Build fast, SEO-optimized static sites with Docusaurus v3.9.2 using Markdown/MDX, SEO metadata, and plugins. Helps with setup, docs, SEO optimization, plugin integration, and GitHub Pages deployment.
generating-stitch-screens
>
scripting-bash
Master defensive Bash scripting for production automation, CI/CD pipelines, and system utilities. Expert in safe, portable, and testable shell scripts with POSIX compliance, modern Bash 5.x features, and comprehensive error handling. Use when writing shell scripts, bash automation, CI/CD scripts, system utilities, or mentions "bash", "shell script", "automation", "defensive programming", or needs production-grade shell code.
playwright-cli
>-
ralph-loop
Execute an autonomous development loop that picks one task per iteration, implements it, verifies it, and commits the result — each iteration in a fresh context window. Use when user runs /ralph, mentions "ralph loop", "autonomous loop", "builder verifier", "run tasks automatically", "iterate on tasks", "develop autonomously", or wants an automated build-verify-commit cycle with task tracking.
plugin-release-checker
Validate plugin content quality before release. Run skill-validator across plugins, verify marketplace.json completeness, check plugin.json version consistency, and detect broken documentation cross-references. Use when preparing a release, before running release.sh, or when user mentions "release check", "pre-release", "plugin-release-checker", or "release validation".
skill-validator
Validate skills against Anthropic best practices for frontmatter, structure, content, file organization, hooks, MCP, and security (62 rules in 8 categories). Use when creating new skills, updating existing skills, before publishing skills, reviewing skill quality, or when user mentions "validate skill", "check skill", "skill best practices", "skill review", or "lint skill".
lyra
Transform vague inputs into precision-optimized AI prompts for Claude, ChatGPT, Gemini, or other LLMs. Use when user mentions "optimize prompt", "improve prompt", "lyra", "prompt engineering", or needs help crafting effective AI prompts.
deep-research
>
sdlc-develop
Orchestrates 6-phase SDLC pipeline (discovery, requirements, architecture, workstreams, implementation, summary) for guided feature development. Use when user runs /core:develop command, requests spec-driven development, wants to create implementation plans with architecture decisions, or mentions "SDLC", "spec-driven", "plan feature", "development pipeline". Supports plan persistence, wave-based resume, autonomous mode, and architecture/implementation verification.
workflow-orchestration
>
Page 1172 of 1445 · 72242 results