Results for “e-e-a-t”

Defamiliarization audit for empirical output. Systematically interrogates every feature of a figure, table, or set of results — not just the main finding. Named for Jason Fletcher, who asked about the spike at t=1 when everyone else was looking at t=2. Use when you have output and are about to interpret or report it.

Search the web, extract content from URLs, and crawl websites using the Tavily API.

Bypass the Windows Antimalware Scan Interface (AMSI) using memory patching, reflection, and obfuscation techniques. Execute undetected PowerShell, VBScript, JScript, and .NET assemblies in-memory without triggering Microsoft Defender or third-party AV/EDR solutions. Use this skill during Red Team engagements when loading offensive tools (Mimikatz, Rubeus, SharpHound) in memory on defended Windows endpoints.

Set up, audit, and debug analytics tracking implementations including GA4, Google Tag Manager, event taxonomy, and conversion tracking.

Use when delivery work needs structuring into epics — defining a new epic, refining or superseding an existing one, or decomposing a PRD's requirements into durable delivery structures that feed issue decomposition. Writes docs/product/epics/NN-<slug>.md (durable, id-stable, superseded-never-deleted), each epic tracing to the JTBD ids it serves and the PRD requirement IDs it bundles. In the A-Team pipeline this is a definition-phase output ("the Epics"). Do not use for full roadmap/portfolio planning across quarters (deliberately not ported), for delivery tickets or acceptance criteria (ticket-writer), or to create or revise jobs (jobs-to-be-done).

Design and validate model-facing tool definitions with clear names, action-oriented descriptions, bounded JSON Schema parameters, explicit side effects, safe defaults, idempotency, errors, and realistic tests. Use when creating function-calling tools, MCP tools, agent actions, structured tool inputs, or when a model selects the wrong tool, invents arguments, or causes unsafe side effects.

Evaluate scientific claims and evidence quality by assessing experimental design, identifying biases and confounders, and applying evidence grading frameworks like GRADE and Cochrane Risk of Bias.

Provides guidance on using the new .NET 10 cross-platform safe area API for edge-to-edge layouts, keyboard avoidance, and migration from legacy iOS-only APIs.

Debug LangChain and LangGraph agents by fetching execution traces from LangSmith Studio. Use when debugging agent behavior, investigating errors, analyzing tool calls, checking memory operations, or examining agent performance. Automatically fetches recent traces and analyzes execution patterns. Requires langsmith-fetch CLI installed.

Migrates OSGi EventAdmin handlers and JCR EventListeners to AEM Cloud Service-compliant patterns, including EventHandler+JobConsumer split, routing rules, and leader-only execution.

Extract full product details from Taobao or Tmall product pages by item ID, including title, price, shop info, images, SKU variants, and attributes.

Enforce deploy-time security controls that ensure only trusted, attested container images are deployed to Google Kubernetes Engine and Cloud Run.

Audit server-side paid-media measurement, including tag management, conversion APIs, event taxonomy, deduplication, consent, hashing, data quality, and observability.

All-in-one fullstack dev engine. /aura: 46 modes (build/fix/clean/deploy/review/spec/lore/ax/experiment/payment/debug/qa/orchestrate/escalate+), 6-layer security with 32 hooks, tiered models (ZERO/ECO/PRO/MAX), 8 languages, 16 specialized agents, SPEC/EARS/TRUST5/XLOOP/RALF/Autopus absorbed. ~55% token savings.

Evidence-first repo execution workflow for ECC. Use when the user wants a command run, a repo checked, a CI failure debugged, or a narrow fix pushed with exact proof of what was executed and verified.

Upscale and enhance images using Real-ESRGAN, Thera, FLUX Upscaler, and Topaz via the inference.sh CLI.

Provides real-time access to SEC EDGAR filings, BLS employment statistics, and USDA crop prices through three MCP tools.

This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

Expert photography prompt engineer specializing in crafting detailed, evocative prompts for AI image generation. Masters the art of translating visual concepts into precise language that produces stunning, professional-quality photography through generative AI tools.

Use to prove that a support process, policy or script change actually took effect — when, for whom, and whether behaviour followed — rather than that it was approved. Trigger for "prove we made that change", "when did this policy actually change", "did the team adopt the new process", evidencing remediation, "we told everyone" claims, or a change that was signed off and never landed.

Structure the first 90 days of a VP or CPO transition as a diagnostic process, not an execution sprint, using a three-phase playbook to build evidence before making decisions.

MUX Architect IA — Expert en architecture UX technique, CSS systems, motion design systems, et implementation developer-friendly. Pont entre design et code.

Use when planning an ASE (IEEE/ACM Automated Software Engineering) research-track campaign backward from the deadline, through abstract registration, the double-anonymous submission, the early-rejection gate, rebuttal, the criteria-bound revision round, artifact evaluation, and the camera-ready in both IEEE Xplore and the ACM Digital Library.

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

Organiza y guarda memoria en Engram automáticamente, clasificando cada conocimiento por tipo y área, y consultando el contexto al iniciar sesión.

Runs and interprets Elixir/Phoenix tooling (mix test, credo, dialyzer, format), generates OTP-conforming modules, and helps with Ecto and LiveView patterns.

Provides structured goal-setting and strategic guidance in the style of John Doerr, focusing on OKRs, execution, and team evaluation.

CONDOR v2.0 — Multi-Asset Thesis Picker. Evaluates BTC, ETH, SOL, HYPE simultaneously and enters the strongest thesis. Conviction-scaled margin. DSL exit managed by plugin runtime via runtime.yaml.

Create new skills, modify existing ones, and measure their performance through iterative evaluation and benchmarking.

Write a PRD or feature spec that aligns design and engineering — problem with evidence, explicit non-goals, measurable success metrics, and testable acceptance criteria.

Detects and responds to OAuth token theft and replay attacks in cloud environments, focusing on Microsoft Entra ID token protection, conditional access policies, and sign-in anomaly detection.

This skill recommends performing an imaging study to assess tumor size, appearance, and parasellar extent once biochemical diagnosis of acromegaly is confirmed. Trigger when IGF-1 is elevated and GH fails to suppress to <0.4 µg/L during an oral glucose tolerance test.

Determines whether to perform adrenal venous sampling (AVS) to lateralize aldosterone excess in patients with confirmed primary aldosteronism (PA) who are being evaluated for surgical treatment. Indicated when surgery is feasible and desired by the patient, or when subtype workup is planned for a surgical candidate, especially in those younger than 35 years with spontaneous hypokalemia, marked aldosterone excess, and unilateral adrenal lesions on CT.

Benchmarks long-context language models across 20 sub-tasks spanning 3k–200k tokens, covering retrieval, reasoning, summarization, and instruction understanding, with exact-match accuracy as the primary metric.