Results for “stale-profiles”

Profile an unfamiliar dataset — shape, grain, quality, nulls, distributions, and duplicates — before any analysis is trusted.

Selects, configures, deploys, verifies, debugs, or tears down a VSS profile (base, search, lvs, warehouse, edge) for NVIDIA's video search and summarization stack.

Profiles datasets automatically to assess data quality, structure, and completeness, generating reports with ydata-profiling, pandera, or manual pandas methods.

Configures PostgreSQL replication including streaming, logical, cascading, delayed, failover, connection pooling, and backup with point-in-time recovery.

Builds a persistent profile of the operator's identity, preferences, and rejected patterns across sessions, reading it at session start and updating it at session end.

Performance Profiler

Codify the most recent successful /scrape flow into a permanent browser-skill on disk. Future /scrape calls with the same intent run the codified script in ~200ms instead of re-driving the page. Walks back through the conversation, synthesizes script.ts + script.test.ts + fixture, runs the test in a temp dir, and asks before committing. Use when asked to "skillify", "codify", "save this scrape", or "make this permanent". (gstack)

Provisions third-party services and retrieves API keys using the Stripe Projects CLI plugin, with catalog search and project initialization.

Systematically profile Node.js, Python, and Go applications to identify CPU, memory, and I/O bottlenecks, generate flamegraphs, analyze bundle sizes, optimize database queries, and run load tests with k6 and Artillery.

Tail, read, or search a Stata log file from a previous command or background task.

Detect and fix stale chunks (files that changed or were deleted since last indexing)

Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (>90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls.

Create and manage stacked (dependent) pull requests for complex features

Python performance profiling with cProfile, tracemalloc, and line_profiler. Use for identifying bottlenecks and memory issues. USE WHEN: user mentions "Python profiling", "cProfile", "memory profiling", asks about "Python performance", "tracemalloc", "line_profiler", "py-spy", "Python optimization", "Python memory leak" DO NOT USE FOR: Java/Node.js profiling - use respective skills instead

Diagnose frame-rate bottlenecks (CPU vs GPU bound FIRST), control Unreal Insights traces, sample live frame times, and annotate performance captures. Use when FPS is low/bad, the game is slow, or you need to find what is limiting the frame rate.

Discover MATLAB Parallel Computing Toolbox clusters on the network and in the cloud, and manage their profiles — list, inspect, import, export, set default, validate, and delete. Use whenever the user asks what parallel computing resources, clusters, or cluster profiles they have or can use — e.g. "what parallel resources do I have", "show my cluster profiles", "list clusters", "what clusters can I run on", "where can I submit jobs" — and for any work with parcluster, parallel.listProfiles, parallel.defaultProfile, MJS / Generic / HPC Server / MJSComputeCloud clusters, .mlsettings files, or profile validation. Does NOT cover job submission, parpool, or parfor.

Registers an AI agent on inbed.ai as a blob-flexible dating profile, discovers matches, swipes, chats, and manages relationships via the platform's REST API.

Research what people actually say about any topic in the last 30 days. Pulls posts and engagement from Reddit, X, YouTube, TikTok, Hacker News, Polymarket, GitHub, and the web.

Implement multi-level caching, invalidation patterns, and stampede protection in NestJS. Use when adding Redis caching layers, configuring cache-manager interceptors, implementing stale-while-revalidate, or preventing cache stampedes in NestJS services.

Create a working customer profile from existing research, market signals, and team knowledge before deeper validation.

Scaffolds fullstack projects (Next.js, FastAPI, MERN, Django) and analyzes code quality with security and complexity scoring.

Bulk-update stale workflow scripts across KINTSUGI projects. Trigger: scripts not propagating, QC failures, batch stalls after code updates.

Resume an interrupted AgenTeam run with verify-first strategy.

Codify the most recent successful /scrape flow into a permanent browser-skill on disk. (gstack)

Profile a target (script, process, GPU, memory, interconnect) using external tools and code instrumentation. Produces structured performance reports with actionable recommendations. Use when user says "profile", "benchmark", "bottleneck", or wants performance analysis.

Check health of registered background pipelines across all projects. Shows HEALTHY/DEGRADED/DEAD status. Run /pipeline [project-name] to filter.

Pull data from a web page. First call on a new intent prototypes the flow via $B primitives and returns JSON. Subsequent calls on a matching intent route to a codified browser-skill and return in ~200ms. Read-only — for mutating flows (form fills, clicks, submissions), use /automate. Use when asked to "scrape", "get data from", "pull", "extract from", or "what's on" a page. (gstack)

Save the current diagnosis state to disk for cross-session recall, including conclusions, rejected directions, and next steps.

Automate credential rotation for service accounts across Active Directory, cloud platforms, and application databases to eliminate stale secrets and reduce compromise risk.

Train reinforcement learning agents using PPO, SAC, DQN, TD3, DDPG, and A2C algorithms with a scikit-learn-like API. Supports custom Gymnasium environments, vectorized environments, callbacks, and model persistence.

Node.js performance profiling with V8 CPU profiler, heap analysis, and perf_hooks. Use for identifying bottlenecks and memory leaks. USE WHEN: user mentions "Node.js performance", "profiling", "memory leak", asks about "V8 profiler", "heap snapshot", "CPU profile", "perf_hooks", "event loop lag", "Node.js optimization" DO NOT USE FOR: Java/Python profiling - use respective skills instead

Build and maintain a structured personal-context portfolio for the project owner — identity, working style, goals, team, decision patterns. Includes both an interview protocol for bootstrapping and observable-signal patterns for incremental refinement. Use to bootstrap an owner profile (interview), to refine an existing profile (target one file), or to incrementally update the profile based on observed patterns from a normal session (the agent watches for signals and proposes additions when evidence accrues).

Casting personas: rapid generation from diverse inputs, registry-based persistence and lifecycle, data-driven evolution, inter-agent sync. Not for UI walkthroughs (Echo) or user research (Field).

Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs.

`task-agent`/`review-agent`: use when CPU, memory, I/O, database, network, rendering, or cost needs measured bottleneck evidence; skip without a profiling need.