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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.

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This skill outlines monitoring glucocorticoid replacement in children with primary adrenal insufficiency (PAI) using clinical assessment of growth velocity, weight, blood pressure, and energy levels. Trigger when evaluating a child with PAI for adequacy of glucocorticoid therapy during routine follow-up.

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Applies serum cortisol cutoffs (<3 μg/dL indicates central adrenal insufficiency; >15 μg/dL likely excludes it) when evaluating morning cortisol for suspected adrenal insufficiency. Triggers include morning cortisol measurement in suspected AI and use when interpreting morning cortisol levels for adrenal insufficiency workup.

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Accounts for estrogen-induced elevation of total serum cortisol via increased corticosteroid-binding globulin (CBG) when evaluating adrenal reserve or hydrocortisone replacement adequacy. Triggered when assessing glucocorticoid adequacy in patients receiving estrogen therapy (e.g., oral estrogen replacement) or interpreting cortisol levels in estrogen-exposed individuals.

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The Endocrine Society guideline recommends against routine hormonal monitoring of glucocorticoid replacement in primary adrenal insufficiency and advises adjusting therapy solely based on clinical response. Use when evaluating glucocorticoid dose adequacy, such as when patients report fatigue, weight loss, hypotension, or signs of Cushingoid over-replacement.

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Recommends measurement of plasma ACTH to establish primary adrenal insufficiency (PAI) diagnosis in patients with confirmed cortisol deficiency; a plasma ACTH concentration ≥2-fold the upper limit of the reference range supports PAI. Use when evaluating plasma ACTH in a patient with low morning cortisol or abnormal corticotropin stimulation test.

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In patients with normal preoperative adrenal function, suggests an individualized clinical approach for postoperative glucocorticoid administration until HPA axis evaluation can be performed. Triggers include managing postoperative patient with normal preoperative adrenal function needing glucocorticoid management.

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Recommends against using a random cortisol level to diagnose adrenal insufficiency. Triggers when considering a random cortisol test for AI evaluation (e.g., "random cortisol measurement being considered for AI diagnosis").

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Capture what someone actually said without contaminating it with your own inference. Invoke when eliciting intent in conversation (design discussion, requirement interview, decision surfacing) and when turning a conversation into a durable record (ADR, decision node, memory entry, spec `## Decisions` row). Enforces quote-before-critique, keeps illustration separate from commitment, and holds interpretation subordinate to verbatim. Prevents the failure where unspecified space is filled by the recorder and then evaluated as if the speaker had specified it.

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lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).

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Analyze NFT projects for investment decisions — evaluate fundamentals, identify red flags, assess risk, and provide buy/hold/avoid recommendations

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Evaluate and maximize GitHub repo quality from 7/10 to 10/10 perfect

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High-level SDK for Azure AI Foundry projects with agents, connections, deployments, and evaluations.

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Azure AI Projects SDK for .NET. High-level client for Azure AI Foundry projects including agents, connections, datasets, deployments, evaluations, and indexes.

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Azure AI Projects SDK for Java. High-level SDK for Azure AI Foundry project management including connections, datasets, indexes, and evaluations.

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Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.

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Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.

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A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.

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Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

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Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).

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Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks

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Run the LangSmith evaluation suite and display pass/fail results

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Add a new E2E test case to tests/e2e/prompts.yaml for LangSmith evaluation. Use when adding interaction pairs to test, covering new ANSM drug classes, or rebalancing eval coverage.

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Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance validation.

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