226 skills · sorted by relevance
Compressive Vasomotion Hypothesis (CVH) — vasomotion as a fast compression sweep that collapses ambivalent neural resonances (the Bayesian-blur problem) into a definite state. Use when modeling the ~100ms taṇhā 'grab', precision-weighting as compression forcefulness, or the generative collapse step of vasocomputational active inference.
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Evaluates netting benefits across derivative portfolios with bilateral vs cleared netting, portfolio compression, and capital savings. Use when analyzing netting efficiency, evaluating compression opportunities, or optimizing counterparty exposure.
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Analyze a tensegrity system by identifying compression struts and tension cables, classifying type (class 1/2, biological/architectural), computing prestress equilibrium, verifying stability via Maxwell's rigidity criterion, and mapping biological tensegrity (microtubules, actin, intermediate filaments). Use when evaluating tensegrity in architecture, robotics, cell biology, or any system with isolated compression in continuous tension.
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Design and evaluate context compression strategies for long-running agent sessions. Use when agents exhaust memory, need to summarize conversation history, or when optimizing tokens-per-task rather than tokens-per-request.
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Use when a task needs the judgment of a Diagnostic Medical Sonographer — deciding whether a duplex, compression, or graded-compression ultrasound study is diagnostic versus technically limited, choosing when to interrupt a scanning protocol to escalate a real-time critical finding, setting scan technique and ALARA (TI/MI) parameters for a given exam type, or drafting the technical worksheet and preliminary findings a physician will interpret and sign.
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Choose what kind of knowledge to transfer between teacher and student models: response, feature, or relational, and decide among offline, online, self, or cross-modal distillation schemes. Best for distillation strategy selection, capacity-gap diagnosis, and transfer planning. Activate on "knowledge distillation", "teacher-student", "soft labels", "feature distillation", "online distillation", or "cross-modal transfer". NOT for generic compression checklists or unrelated training work.
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This skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding context limits.
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Identifies and unpacks UPX-packed and other packed malware samples to expose the original executable code for static analysis. Covers both standard UPX unpacking and handling modified UPX headers that prevent automated decompression. Activates for requests involving malware unpacking, UPX decompression, packer removal, or preparing packed samples for analysis.
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Expert en ingénierie du contexte IA (compression de prompts, chunking, gestion tokens, optimisation fenêtre)
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Expert en ingénierie audio (mixage, mastering, podcast editing, réduction de bruit, EQ, compression)
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Expert en optimisation des coûts d'agents IA (sélection modèle, caching, compression prompts, budgeting tokens)
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Identifies and unpacks UPX-packed and other packed malware samples to expose the original executable code for static analysis. Covers both standard UPX unpacking and handling modified UPX headers that prevent automated decompression. Activates for requests involving malware unpacking, UPX decompression, packer removal, or preparing packed samples for analysis.
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Identifies and unpacks UPX-packed and other packed malware samples to expose the original executable code for static analysis. Covers both standard UPX unpacking and handling modified UPX headers that prevent automated decompression. Activates for requests involving malware unpacking, UPX decompression, packer removal, or preparing packed samples for analysis.
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Look up commands for concise response modes, commit messages, review comments, and Markdown compression. The reference also explains how to check the current mode, return to normal responses, and configure startup defaults.
Compress agent replies into short phrases while preserving technical details, negations, numbers, and exact commands. Use it to reduce repeated explanations and keep chat responses brief until you explicitly turn the mode off.
Connect AI agents to OmniRoute through MCP, a protocol for accessing tools. Use tools for request routing, memory, cache, providers, and audits, with three connection methods and permission scopes that control which operations are available.
Preserve project decisions and work progress across sessions, and share information between agents. Organize stored knowledge into separate spaces, retrieve relevant records, and manage expiration, compression, and cleanup of saved data.
Measure the total size of a web page and its resources, identify what slows loading, and reduce unnecessary weight. Use a 1500KB limit to guide image optimization, code compression, and removal of unused resources.
Inspect compressed JavaScript bundles, the files that package application code, to find excessive size and loading costs. Recommend splitting code, removing unused portions, and reviewing dependencies based on measured effects on page responsiveness.
Review website images for file format, size, dimensions, and loading behavior. Produce improved HTML with image variants for different screen sizes, suitable compression, and deferred loading where appropriate, while addressing loading speed and layout shifts.
Review website images and delivery settings to introduce AVIF, an image format with efficient compression. Check image size and loading behavior, and provide WebP or JPEG alternatives for browsers that do not support AVIF.
Process video and audio with FFmpeg for editing and publishing. Convert formats, resize and compress files, extract audio, trim clips, and change playback speed. Includes recipes for preparing Remotion assets and exporting videos for social platforms and websites.
Compress screen recordings on Apple Silicon Macs using dedicated video hardware. Choose quality settings for sharing or archiving, inspect video properties, and check the resulting file size and storage savings.
Design and evaluate how an AI agent remembers user preferences and history across conversations. Compare storage formats and memory frameworks, plan updates and compression, and distinguish personal memory from shared document retrieval while addressing sensitive information.