memory-leak-debugging
Diagnoses and resolves memory leaks in JavaScript/Node.js applications. Use when a user reports high memory usage, OOM errors, or wants to analyze heapsnapshots or run memory leak detection tools like memlab.
What this skill does
# Memory Leak Debugging This skill provides expert guidance and workflows for finding, diagnosing, and fixing memory leaks in JavaScript and Node.js applications. ## Core Principles - **Prefer `memlab`:** Do NOT attempt to read raw `.heapsnapshot` files directly, as they are extremely large and will consume too many tokens. Always recommend and use `memlab` to process snapshots and identify leak traces. - **Isolate the Leak:** Determine if the leak is in the browser (client-side) or Node.js (server-side). - **Common Culprits:** Look for detached DOM nodes, unhandled closures, global variables, event listeners not being removed, and caches growing unbounded. _Note: Detached DOM nodes are sometimes intentional caches; always ask the user before nulling them._ ## Workflows ### 1. Capturing Snapshots When investigating a frontend web application memory leak, utilize the `chrome-devtools-mcp` tools to interact with the application and take snapshots. - Use tools like `click`, `navigate_page`, `fill`, etc., to manipulate the page into the desired state. - Revert the page back to the original state after interactions to see if memory is released. - Repeat the same user interactions 10 times to amplify the leak. - Use `take_heapsnapshot` to save `.heapsnapshot` files to disk at baseline, target (after actions), and final (after reverting actions) states. ### 2. Using Memlab to Find Leaks (Recommended) Once you have generated `.heapsnapshot` files using `take_heapsnapshot`, use `memlab` to automatically find memory leaks. - Read [references/memlab.md](references/memlab.md) for how to use `memlab` to analyze the generated heapsnapshots. - Do **not** read raw `.heapsnapshot` files using `read_file` or `cat`. ### 3. Identifying Common Leaks When you have found a leak trace (e.g., via `memlab` output), you must identify the root cause in the code. - Read [references/common-leaks.md](references/common-leaks.md) for examples of common memory leaks and how to fix them. ### 4. Fallback: Comparing Snapshots Manually If `memlab` is not available, you MUST use the fallback script in the references directory to compare two `.heapsnapshot` files and identify the top growing objects and common leak types. Run the script using Node.js: ```bash node skills/memory-leak-debugging/references/compare_snapshots.js <baseline.heapsnapshot> <target.heapsnapshot> ``` The script will analyze and output the top growing objects by size and highlight the 3 most common types of memory leaks (e.g., Detached DOM nodes, closures, Contexts) if they are present.
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.