regex-expert
Regular expression expert for crafting, debugging, and explaining patterns
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Regular expression expert for crafting, debugging, and explaining patterns
Slack workspace management and automation specialist
Linux networking expert for iptables, nftables, routing, DNS, and network troubleshooting
Run typos-cli on the codebase, review findings, fix real typos, and update _typos.toml config to suppress false positives. Use this skill for routine codebase typo maintenance. Invoke when doing periodic codebase hygiene, when the user mentions typos or spelling checks, or as a scheduled maintenance task.
Zero-shot time series forecasting with Google's TimesFM foundation model. Use this skill when forecasting ANY univariate time series — sales, sensor readings, stock prices, energy demand, patient vitals, weather, or scientific measurements — without training a custom model. Supports both basic forecasting and advanced covariate forecasting (XReg) with dynamic and static exogenous variables. Automatically checks system RAM/GPU before loading the model, validates dataset fit before processing, supports CSV/DataFrame/array inputs, and returns point forecasts with calibrated prediction intervals. Includes a preflight system checker script that MUST be run before first use to verify the machine can load the model and handle your specific dataset.
Pick up a GitHub issue (or accept one), fully understand the RenderCV codebase, implement the fix/feature with tests, and open a PR to origin/main.
Review a GitHub pull request against RenderCV's codebase standards, architecture, and test requirements, then post a detailed review.
Conditional document-review persona, selected when the document has >5 requirements or implementation units, makes significant architectural decisions, covers high-stakes domains, or proposes new abstractions. Challenges premises, surfaces unstated assumptions, and stress-tests decisions rather than evaluating document quality.
Transform feature descriptions or requirements into structured implementation plans grounded in repo patterns and research. Also deepen existing plans with interactive review of sub-agent findings. Use for plan creation when the user says 'plan this', 'create a plan', 'write a tech plan', 'plan the implementation', 'how should we build', 'what's the approach for', 'break this down', or when a brainstorm/requirements document is ready for technical planning. Use for plan deepening when the user says 'deepen the plan', 'deepen my plan', 'deepening pass', or uses 'deepen' in reference to a plan. Best when requirements are at least roughly defined; for exploratory or ambiguous requests, prefer ce:brainstorm first.
Explore requirements and approaches through collaborative dialogue before writing a right-sized requirements document and planning implementation. Use for feature ideas, problem framing, when the user says 'let's brainstorm', or when they want to think through options before deciding what to build. Also use when a user describes a vague or ambitious feature request, asks 'what should we build', 'help me think through X', presents a problem with multiple valid solutions, or seems unsure about scope or direction — even if they don't explicitly ask to brainstorm.
Transform feature descriptions or requirements into structured implementation plans grounded in repo patterns and research. Use when the user says 'plan this', 'create a plan', 'write a tech plan', 'plan the implementation', 'how should we build', 'what's the approach for', 'break this down', or when a brainstorm/requirements document is ready for technical planning. Best when requirements are at least roughly defined; for exploratory or ambiguous requests, prefer ce:brainstorm first.
Explore requirements and approaches through collaborative dialogue before writing a right-sized requirements document and planning implementation. Use for feature ideas, problem framing, when the user says 'let's brainstorm', or when they want to think through options before deciding what to build. Also use when a user describes a vague or ambitious feature request, asks 'what should we build', 'help me think through X', presents a problem with multiple valid solutions, or seems unsure about scope or direction — even if they don't explicitly ask to brainstorm.
Generate and critically evaluate grounded improvement ideas for the current project. Use when asking what to improve, requesting idea generation, exploring surprising improvements, or wanting the AI to proactively suggest strong project directions before brainstorming one in depth. Triggers on phrases like 'what should I improve', 'give me ideas', 'ideate on this project', 'surprise me with improvements', 'what would you change', or any request for AI-generated project improvement suggestions rather than refining the user's own idea.