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概要と使いどころ
Exploit advanced HTTP Request Smuggling combining Transfer-Encoding vulnerabilities (TE.TE). By obscuring the Transfer-Encoding header, an attacker forces desynchronization between a frontend proxy (which processes the request one way) and the backend server (which processes it another way), allowing the smuggling of malicious requests to bypass security controls or poison caches.
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Penetration test AWS cloud environments for misconfigurations, privilege escalation, data exposure, and lateral movement. Use this skill when assessing AWS accounts for security weaknesses including S3 bucket misconfigurations, IAM policy flaws, EC2 metadata exploitation, Lambda function abuse, and cross-account attack paths. Covers both external and authenticated AWS pentesting.
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Test APIs for authentication and authorization bypass vulnerabilities including JWT manipulation, OAuth2 flaws, API key leakage, broken authentication, and token forgery. Use this skill when assessing REST/GraphQL APIs for access control weaknesses, session management flaws, or credential handling issues. Covers JWT algorithm confusion, OAuth redirect manipulation, and rate limit bypass.
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Analyzes CVE vulnerabilities in project dependencies with code path tracing and PoC generation for Burp Suite. Traces vulnerable code from user input to sink, assesses exploitability, and generates HTTP requests for testing.
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Prepare flawless design-to-development handoffs with specs, assets, behaviors, and QA processes.
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Post-mortem analysis of a PhysicsIntern workspace run (Claude Code, Pi, Codex, or OpenCode host). Reconstructs the trajectory from the session record — JSONL file(s) for Claude/Pi/Codex, the SQLite store for OpenCode — audits methodology adherence against the workspace's own CLAUDE.md / AGENTS.md and skill/agent prompts, checks commit discipline and flag dispositions, and assesses substantive quality. Produces a thorough evidence-anchored markdown report. Use after a workspace has been worked on to identify what went well, where the methodology slipped, and what prompts to improve.
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Audit essays, reports, literature reviews, dissertations, proposals, and source-backed assignments for high-score academic quality. Use when the user asks whether a paper can get a high grade, wants teacher/rubric feedback addressed, needs a pre-submission review, or needs checks for strict rubric compliance, academic standards, prompt/rubric alignment, argument quality, comparative analysis, evidence hierarchy, table/figure integration, citation specificity, conclusion strength, academic language, source-claim integrity, or evidence boundaries.
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Use when the user wants their way of working with Claude assessed — "review my session", "how am I using Claude Code", "audit my setup / workflow", "am I following best practices", "coach me", "what should I improve" — or pastes a Claude.ai/Cowork/Tag transcript and asks how they could have worked better. Do NOT use for reviewing code changes (that is code review) or for teaching a product from scratch (use academy-learn); this skill only reviews how the human works with Claude.
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Detects packing and encryption by measuring Shannon entropy across a binary's sections and regions: flagging high-entropy executable sections, entropy spikes, and size/raw-vs-virtual anomalies that indicate compression or encryption. Activates for requests to measure entropy, detect packing, or assess whether a sample is compressed/encrypted.
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Uses Ghidra to disassemble and decompile a binary, navigate to key routines via imports and strings, annotate decompiled code, and run headless scripts to automate extraction of C2, crypto, and config. Activates for requests to reverse engineer with Ghidra, decompile a binary, or script Ghidra headless analysis.
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The measurement surface for ALL Pulp DSP and audio-pipeline work — read it BEFORE writing or gating DSP, not only when something already sounds wrong. Covers the C++ harness (signal generators, metrics, assertions, RenderScenario, contracts), the offline Audio Doctor (magnitude/frequency response, THD/THD+N, phase/group delay), and their Python sibling the Audio Quality Lab (tools/audio/quality-lab — null residual + alignment, LTAS log-spectral distance, spectral flux/centroid, HNR, Theil-Sen drift slope, Kaiser-sinc resampling, license-guarded corpus, regression-net ratchet). TRIGGER on AUTHORING work — "build/design an oscillator/filter/synth/effect", "add a DSP module", "what should the acceptance gate be", "how do I measure aliasing / anti-aliasing / alias floor", "null against a reference", "is this DSP correct", "choose a tolerance", "golden/regression corpus for audio", "measure drift or jitter", "A/B two renders" — AND on DEBUGGING work — "is there sound / no audio / I hear nothing", "does this filter/compressor/synth/delay produce the right signal", "prove the DSP / prove the contract", "measure the frequency response", "what's the THD / is it distorting", "what's the group delay / phase response / measured latency", "magnitude response curve", "render a test tone and assert", "audio regression", "64-frame works but 128 is silent", "sample-rate change pitch-shifted it", "describe what's in this buffer", "audio doctor", "compare before/after a DSP refactor". Reach for this BEFORE hand-rolling any FFT, null test, alias measurement, pitch tracker, or golden-render script — most of it already exists in one of the two lanes. Test/tool layer over HeadlessHost — deterministic, no audio device, no speakers. Off the realtime thread entirely.
日本語の概要は準備中です。原文の説明を表示しています。
Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.
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Refreshes the AssetDatabase. Use it if any file was added or updated in the project outside of Unity API. Use it if need to force scripts recompilation when '.cs' file changed.
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Close currently opened prefab. Use it when you are in prefab editing mode in Unity Editor. Use 'assets-prefab-open' tool to open a prefab first.
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Open prefab edit mode for a specific GameObject. In the Edit mode you can modify the prefab. The modification will be applied to all instances of the prefab across the project. Note: Please use 'assets-prefab-close' tool later to exit prefab editing mode.
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Create a prefab from a GameObject in the current active scene. The prefab will be saved in the project assets at the specified path. Use 'gameobject-find' tool to find the target GameObject first.
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Save a prefab. Use it when you are in prefab editing mode in Unity Editor. Use 'assets-prefab-open' tool to open a prefab first.
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Emergency fix workflow that bypasses normal sprint processes with a full audit trail. Creates hotfix branch, tracks approvals, and ensures the fix is backported correctly.
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Unity New Input System correctness patterns. Catches common mistakes with action reading (triggered vs IsPressed vs WasPressedThisFrame), action map switching, rebinding persistence, InputValue lifetime, PassThrough vs Value, local multiplayer device assignment, and control scheme auto-switching. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. Based on Unity 6.3 LTS.
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用于设计、实现或审查前后端 API 集成、类型化 API client、REST/tRPC/OpenAPI 客户端选型、认证刷新、API 错误映射、上传流程、SSE/WebSocket/轮询选择、CORS 相关前端行为或跨边界 loading/error 状态。不要用于纯后端服务架构或仅 TanStack Query 缓存策略；中文触发词包括 API 集成、前后端联调、typed API client、接口错误处理、SSE、WebSocket。
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Use when designing, implementing, or reviewing frontend-to-backend API integration, typed API clients, REST/tRPC/OpenAPI client choices, auth refresh, API error mapping, upload flows, SSE/WebSocket/polling choices, CORS-facing frontend behavior, or cross-boundary loading/error states. Do not use for backend-only service architecture or TanStack Query cache policy alone; Chinese triggers include API integration, front-end and back-end joint debugging, typed API client, Interface error handling, SSE, WebSocket.
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Use when a task needs the judgment of a drywall and ceiling tile installer — specifying a fire-rated wall/ceiling assembly to a UL design number, hitting an STC target on a demising wall, choosing board type for a wet area, placing control joints on a long run, or diagnosing why a finished assembly failed inspection or a sound/mold complaint.
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Use when a task needs the judgment of an Electrical and Electronic Equipment Assembler — inspecting a solder joint against the specific IPC/J-STD workmanship standard criteria rather than personal visual judgment, following ESD precautions for every component handled since damage is invisible at the time it occurs, verifying a crimped connection with a pull test rather than visual inspection alone, or treating a single suspected cold joint as a potential complete failure point rather than a minor defect.
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Use when a task needs the judgment of an environmental scientist — scoping or reviewing a Phase I/Phase II environmental site assessment, interpreting soil or groundwater sampling results against regulatory action levels, drafting an environmental impact statement or NEPA scoping document, running a contaminant fate-and-transport screening calc, or assessing ecological risk to a receptor.
日本語の概要は準備中です。原文の説明を表示しています。