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Investigate code errors through a structured process using reproduction steps, logs, and testable explanations. The workflow guides fault isolation, fixes, and follow-up checks, with common error patterns for Python, JavaScript/TypeScript, and Bash/Zsh.

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• Investigating an error using logs and reproduction steps
• Finding why code broke after a recent change
• Troubleshooting common shell script errors

Build reproducible empirical analyses in R, from data cleaning to statistical modeling and publication tables and figures. Covers economics, epidemiology, and machine learning approaches to causal inference, which estimates effects of interventions.

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• Build a reproducible R or Quarto analysis workflow
• Compare regression models with progressively added controls
• Test robustness across samples and statistical methods

Build a Python workflow for empirical research, from data cleaning and statistical checks to estimation, robustness checks, and paper-ready tables and figures. Economics is the default, with additional modes for epidemiology, public health, and machine learning for causal inference.

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• Building an end-to-end empirical analysis workflow in Python
• Replicating an applied economics paper
• Producing regression tables and event-study plots

Build a reproducible Stata analysis from data cleaning through modeling, diagnostic checks, and robustness tests. Generate runnable .do files, regression tables, and figures for empirical papers, with additional workflows for epidemiology and machine learning approaches to causal inference.

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• Building a reproducible Stata analysis pipeline
• Comparing regression specifications in a paper table
• Checking causal estimates with robustness tests

Capture a Unity GameObject, an object in a scene, as a PNG with adjustable camera views, backgrounds, and lighting. Isolate the target or include the scene, and combine four views into one image for visual review.

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• Capture an object with a transparent background
• Review an object from four directions
• Compare appearance under different lighting

Combine feedback from users, code, logs, and runtime results into a reasoned plan. Separate agreement from conflicting evidence, explain the judgment, and validate it with the people or systems that supplied the original information.

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• Combining scattered requirements and feedback
• Understanding why stakeholder opinions conflict
• Checking a plan with its actual users

Assess AI agents and MCP tools for malicious instructions, tool misuse, permission violations, and data leaks. The skill organizes checks across applications, identity, data, deployment, and models, with references for each risk area.

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• Review prompt injection risks in AI applications
• Check MCP tool misuse and trust boundaries
• Assess agent permissions and credential misuse

Structure authorized container security tests covering Docker escape, Kubernetes privilege escalation, image vulnerabilities, and network isolation. This skill defines scope, alternative investigation paths, and evidence requirements for reporting demonstrated access and its impact.

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• Define the scope of an authorized container security test
• Review evidence of host access or increased cluster permissions
• Consider other paths when container checks stall

Keep NeMo Relay event histories separate for concurrent requests, tasks, and agents. The skill guides independent scope stacks, which track nested operations, and preserves parent-child relationships when execution crosses asynchronous tasks, threads, or workers.

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• Separate event histories for concurrent requests
• Preserve parent-child links across async tasks and threads
• Prevent request-specific middleware from leaking

Build, migrate, and review adapters that connect external agent runtimes to NVIDIA NeMo Fabric. It guides configuration translation, startup and shutdown, discovery metadata, and validation against the public contract, the rules defining how adapters interact with Fabric.

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• Building an adapter for an external agent runtime
• Migrating an adapter to the public contract
• Reviewing configuration mapping and runtime isolation

Build and debug the shared foundations of DOCA applications on BlueField or ConnectX hardware. Get guidance on device capabilities, memory buffers, context lifecycles, task completion processing, and separate logging controls for the SDK and application.

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• Setting up the foundations of a DOCA application
• Investigating tasks that submit but never complete
• Sharing memory buffers across DOCA libraries

Golang configuration library using spf13/viper — layered precedence (flag > env > file > KV > default), BindPFlag/BindPFlags, SetEnvPrefix + SetEnvKeyReplacer + AutomaticEnv, ReadInConfig + ConfigFileNotFoundError, Unmarshal + mapstructure struct tags, Sub for sub-trees, WatchConfig + OnConfigChange for hot reload, viper.New() for test isolation, and remote KV integration. Apply when using or adopting spf13/viper, or when the codebase imports `github.com/spf13/viper`. For CLI command structure alongside viper, see the `samber/cc-skills-golang@golang-spf13-cobra` skill. For general CLI architecture, see `samber/cc-skills-golang@golang-cli`.

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Comprehensive guide for Go database access — parameterized queries, struct scanning, NULLable columns, transactions, isolation levels, SELECT FOR UPDATE, connection pool, batch processing, context propagation, and migration tooling. Use when writing, reviewing, or debugging Golang code that interacts with PostgreSQL, MariaDB, MySQL, or SQLite; for database testing; or for questions about database/sql, sqlx, or pgx. Does NOT generate database schemas or migration SQL.

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Crabbox/Testbox remote proof: portable provider routing, untrusted isolation, Linux/macOS/Windows/WSL2, live E2E, diagnostics, cleanup.

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Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback

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Plan, deploy, operate, and troubleshoot multi-rack (rack scale) deployments of Azure Local — preintegrated racks scaling to hundreds of machines, built on Network Fabric Controller, Cluster Manager, SAN storage, and managed network fabric. Use for the Microsoft.NetworkCloud and Microsoft.ManagedNetworkFabric control plane. NOT for standard 1-16 node Azure Local, and NOT for rack-aware clusters (two racks as availability zones, up to 8 nodes, synchronous replication) — those are standard scale. WHEN: multi-rack, rack scale Azure Local, aggregation rack, compute rack, Network Fabric Controller, NFC, Cluster Manager, network fabric, isolation domain, az networkcloud, az networkfabric, multi-rack logical network, multi-rack Arc VM.

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Builds, runs, debugs, and operates applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments running inside a container with up to 8 hr lifetimes. Applicable when workloads need strong isolation between tenants, isolated serverless compute, sandbox compute, or secure multi-tenant execution. Also suited for AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs, dev environments running user-supplied code), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, or isolated security scanners. Also applicable when the workload needs long-lived sessions, a real port-listening server (gRPC, WebSocket, custom TCP protocols), state preserved across periods of inactivity (suspend/resume), container-level access (FUSE, eBPF, custom syscalls), or session-affine routing.

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Harden an Attio integration with least-privilege credentials, tenant isolation, log redaction, raw-body webhook verification, idempotency, and incident-ready rotation. Use when reviewing Attio security controls or preparing production access. Trigger with "Attio security", "secure Attio integration", or "Attio webhook signature".

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Separate Adobe development, stage, and production organizations/projects/workspaces, credentials, profiles, storage, events, budgets, and evidence. Use when the task requires adobe multi-environment isolation. Trigger with "Adobe environments", "separate Adobe staging", or "Adobe workspace setup".

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Isolate complex Adobe failures across DNS/TLS, auth, entitlement, schema, async state, storage, Runtime, and downstream layers without leaking credentials or content. Use when the task requires adobe layered failure isolation. Trigger with "deep debug Adobe", "Adobe job stuck", or "Adobe intermittent failure".

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Doctrine for designing and evolving any **SDK** Grida ships — TypeScript, Rust, or otherwise. "SDK" here means a surface that crosses a foreign-or-foreign-treated boundary: published packages, separately-versioned consumers, FFI bindings, public-by-design modules. An SDK's job is to refuse; a strict, honest surface rejects the wrong contents and keeps the package testable in isolation. Default is "core, not customizable"; customization is the exception, defended by a deciding table. Use when authoring or evolving any such surface — `@grida/*` published packages, engine crates (gridaco/nothing `crates/*`) published or FFI-exported, intent/message vocabularies, any contract a second author will compile against. Internal-only helper packages are welcome to follow, not forced. Companion skill for two-sided contract work: $sdk-seam. Critique partners: $pedantic, $etiology. Related: $naming.

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Sandbox escape playbook. Use when breaking out of Python sandbox, Lua sandbox, seccomp filter, chroot jail, container/Docker, browser sandbox, or namespace isolation to achieve unrestricted code execution or file access.

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Guided journey from a large aged codebase everyone fears to touch to one that is safe to change, legible, bounded, and resilient - paid down in place without a rewrite. Orchestrates eight skills phase by phase - working-with-legacy-code, refactoring-patterns, clean-code, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, domain-driven-design - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, REMOVE-TECHNICAL-DEBT-PLAN.md) so the journey resumes across sessions. Use when the user wants to tame a legacy codebase, pay down technical debt safely, avoid a big-bang rewrite, or says 'we are afraid to touch this code'. For a fresh vibe-coded prototype, improve-code-quality; for greenfield structure, design-code-architecture; for a product-and-UX pass, improve-app; to optimize a working codebase for speed, architecture-optimization. For one framework in isolation, invoke that skill directly.

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Guided journey from a raw app idea to a validated, cleanly architected first version that ships on a sustainable cadence. Orchestrates ten skills phase by phase - lean-startup, design-sprint, clean-architecture, domain-driven-design, clean-code, pragmatic-programmer, system-design, ios-hig-design, 37signals-way, software-design-philosophy - asking the user questions at every decision point and recording results in the project docs/ folder (PRODUCT.md, ARCHITECTURE.md, EXPERIMENTS.md, CREATE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to build a new app, validate an idea before writing code, architect an MVP that will not need a rewrite, or says 'help me build my app the right way'. App already exists: use improve-app or grow-app. Business idea not yet validated: run create-business first. Marketing site only: use create-website. Architecture-only question: design-code-architecture. For one framework in isolation, invoke that skill directly.

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