298 skills · sorted by relevance
Manage Namecheap domains and DNS records, which connect domain names to services, through its API. List domains, edit records, switch nameservers, and configure email forwarding, with guidance for initial credentials and allowed IP setup.
Analyze memory dumps with Volatility3 to find heap spraying, an attack that fills memory with attacker-controlled data. Examine suspicious allocations and repeated byte patterns, extract suspicious code, and report affected processes and memory regions in JSON.
Split a multi-call LM workflow by cognitive load, not by accuracy: let one strong model make the few reasoning decisions and a cheap model do the many mechanical executions (Aider architect+editor, DSPy optimizer-LM vs task-LM, vLLM speculative draft+target, LangGraph supervisor+worker are the same shape). Use when designing or cost-optimizing a pipeline that calls an LM many times, when deciding which steps need a strong reasoner vs a cheap executor, or when adding an escalation valve for when the cheap tier degrades. Search keywords: reduce LLM cost, cheaper model, lower token cost, model cascade, route to cheap model, strong model plus cheap model, LLM cost optimization.
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Use when tracking heap allocations on Linux with heaptrack: allocation hotspots, peak heap, temporary allocations, leaks, or a diff of two runs via heaptrack_print. Not for heap errors: use valgrind.
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Find the cheapest AI model that is smart enough for a task, and the cheapest provider to run it on, from live Artificial Analysis benchmarks via Firecrawl. Use when the user asks which model to use, how to cut their LLM or API bill, whether a cheaper model would do, which provider is cheapest or fastest for a model, which open-weights model to self-host, or wants something built with the cheapest model for each step.
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Investigate memory growth and out-of-memory failures in OpenClaw tests. Compare memory measurements and heap snapshots, records of objects held in memory, to distinguish cleanup leaks from retained test modules and verify targeted fixes.
Requires OFOX_API_KEY — create one at https://app.ofox.ai. Generate cheap vertical 9:16 drafts in one priced batch, pick a winner off the contact sheet, then re-render only that one. The cheap tier is the point — several times cheaper per second, so a whole set can cost less than one flagship clip. Use when a user wants Shorts/Reels/TikTok raw material rather than one finished video, e.g. "give me 5 vertical clips to choose from", "a few Reels drafts for this product", "some cheap options before we commit", or "batch me some 9:16 takes". Do not use when one finished clip is wanted — go straight to the scenario skill (seedance-ad-creative, ugc-ads, seedance-short-drama, seedance-product-video), which is also where this skill gets the prompt it drafts.
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Analyze price differences between bond futures and cash bonds, identify the cheapest bond to deliver, and compare implied financing rates with market rates. Present valuation tables and historical context to assess potential basis trades.
Investigate growing memory usage in Qwen Code CLI by comparing heap snapshots, records of objects in memory. Trace what keeps objects alive, identify likely causes, and repeat the workload to verify a fix.
Organize work so an expensive AI model handles planning, judgment, and final review while cheaper helper agents perform bounded research, coding, and testing. Define ownership and verification requirements, then inspect the evidence and integrate their results centrally.
Heap exploitation playbook. Use when targeting ptmalloc2/glibc heap vulnerabilities including UAF, double free, overflow, off-by-one/null, and leveraging tcache/fastbin/unsortedbin attacks for arbitrary write or code execution.
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Heap exploitation playbook. Use when targeting ptmalloc2/glibc heap vulnerabilities including UAF, double free, overflow, off-by-one/null, and leveraging tcache/fastbin/unsortedbin attacks for arbitrary write or code execution.
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Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.
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Glibc heap exploitation — tcache poisoning, unsorted bin leak, IO_FILE FSOP
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Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.
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Analyze V8 heap snapshots to investigate memory leaks and retention issues. Use when given .heapsnapshot files, asked to compare before/after snapshots, asked to find what retains objects, or investigating why objects survive GC. Provides snapshot parsing, comparison, retainer-path helpers, and scratchpad scripts.
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Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.
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Design text extraction for forms, invoices, and quizzes using regex, rules that match text patterns. Check extraction confidence and send uncertain items to an LLM for review, with guidance on testing and tracking processing costs.
Assess whether bonds are expensive, cheap, or fairly priced by comparing yields with government rates and credit risk benchmarks. Combine spread breakdowns, historical context, and interest rate scenarios into tables and a recommendation.
Evaluate companies using projected cash flows, dividends, business segments, and comparisons with peers. Select suitable valuation methods, examine how assumptions change estimated value, and check for problems that can make a seemingly cheap stock misleading.
Review a product requirements document, roadmap, or strategy by challenging the assumptions it depends on. Rank potential failures by impact, likelihood, and testing cost, then propose small tests, evidence to gather, and criteria for stopping or changing course.
Identify which Convex functions drive spending by combining data read per call with call volume. Use deployment evidence or query structure to explain how costs grow with usage and data size, then suggest the cheapest fix for each driver.
Compare estimated AI model costs for a task using its complexity and expected text volume. Get a suitable low-cost recommendation, a cheaper but riskier alternative, and a premium option, with explicit assumptions behind the estimates.
Pressure-test a business or side-hustle idea before you sink money and months into it — find the real demand, the risky assumptions, and the cheapest way to test them. Use when asked to validate my business idea, is this a good business idea, test my side hustle, or should I start this. Produces a read on the core assumptions the idea depends on, who the customer really is and whether the pain is real, the cheapest experiments to test demand before building, a rough viability check (market, competition, economics), and a go/refine/rethink call — honest, not a cheerleader.
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