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Found 11,806 Skills
Document the pitfalls encountered or good practices discovered during this work into searchable learning documents, so that both AI and humans can look them up when similar tasks arise in the future. Two tracks: The pitfall track records experiences where "things should have worked but didn't" — bugs, configuration traps, environment issues, integration failures; The knowledge track records findings that "should be the default approach going forward" — best practices, workflow improvements, reusable patterns. Trigger scenarios: Proactively prompt for input when wrapping up feature-acceptance or issue-fix, or when the user says phrases like "document knowledge", "learning", "document learnings", "record this experience". Spec documents record what was done and how it was done, while learning documents record what pitfalls were encountered / what was learned — the two complement each other and are not interchangeable.
Npm integration. Manage data, records, and automate workflows. Use when the user wants to interact with Npm data.
Beacon integration. Manage data, records, and automate workflows. Use when the user wants to interact with Beacon data.
Replay-first debug flow for SGLang serving problems. Use when a live or recent server shows health-check failures, latency or throughput regressions, queue growth, timeouts, distributed stalls, crash dumps, wrong outputs after deploys, or PD/EP/HiCache issues, and the job is to turn the problem into a replay plus the right next debug tool.
Affinda integration. Manage data, records, and automate workflows. Use when the user wants to interact with Affinda data.
Azure AI Vision integration. Manage data, records, and automate workflows. Use when the user wants to interact with Azure AI Vision data.
Percy integration. Manage data, records, and automate workflows. Use when the user wants to interact with Percy data.
Multi-model agent orchestration using specialized agents for planning, coding, research, math/science, visual analysis, and adversarial review. Use when tasks are complex enough to benefit from different models' strengths, when you want adversarial review to catch blind spots, or when coordinating multi-step workflows across agent roles. Triggers on complex projects, multi-step tasks, architecture decisions, or when explicitly requested.
Ultra-lightweight channel for feature workflows: No need to write design docs, checklists, or conduct phased reviews. Let AI write code directly as it normally would, but before it starts, tell it where the CodeStable knowledge base in the project is and how to search it. This way, the code it writes will have fewer pitfalls and be more consistent with project conventions. Trigger scenarios: Users say "fast mode", "fastforward", "skip all those steps", "just start coding", "help me make xxx" and the requirement is too small to go through the design process.
Phase 3 of the feature workflow – Complete the acceptance closed-loop. Four tasks: 1. Check layer by layer against {slug}-design.md to verify if the implementation deviates from the plan; fix any deviations on the spot instead of just "noting them" in the report. 2. Incorporate this feature into the project's overall architecture documentation. 3. If this feature changes the user story or boundaries of the corresponding requirement, update the requirement doc accordingly. 4. If this feature originated from a roadmap item, change the status of the corresponding entry in roadmap items.yaml to done and sync it with the main document. Finally, produce a {slug}-acceptance.md as the closed-loop proof for the entire workflow. Prerequisite: cs-feat-impl is completed. Trigger scenarios: User says "The feature is done, let's accept it", "Do the final check", "Prepare for merge", "Generate the acceptance report".
Work with the DatoCMS CLI tool (datocms) for command-line migrations, schema type generation, direct one-off CMA calls, typed one-off TypeScript CMA scripts, environment operations, deployment workflows, and multi-project profile syncing. Use when users ask for datocms CLI commands or scripts such as migrations:new, migrations:run, schema:generate, cma:call, cma:docs, cma:script (for ad-hoc typed TypeScript scripts with ambient client/Schema globals), migration scaffolding for models/fields/blocks, CLI setup with datocms.config.json and profiles, OAuth authentication (login, logout, whoami), discovering accessible projects (projects:list), project linking (link, unlink), environment commands (list/fork/promote/rename/destroy), maintenance-mode toggling, CI/CD migration pipelines, blueprint/client project sync, imports from WordPress or Contentful (including assets/content), and CLI plugin management (plugins:install, plugins:add, plugins:available, plugins:link for local plugin development, plugins:remove, plugins:update, plugins:reset, plugins:inspect).
Tomba integration. Manage data, records, and automate workflows. Use when the user wants to interact with Tomba data.