「candidate」の検索結果

Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPseeker (R), HOMER annotatePeaks.pl (CLI), pyranges (Python), GREAT/rGREAT (regulatory domain gene-set enrichment), ChIP-Enrich (locus-length-adjusted), ENCODE SCREEN cCRE classification (PLS/pELS/dELS/CA-CTCF/CA-H3K4me3), and ENCODE-rE2G for cell-type-specific enhancer-gene linking. Handles nearest-TSS vs host-gene ambiguity, promoter window definition, and feature priority. Use when assigning genomic context to peaks, linking enhancer peaks to target genes, classifying peaks against ENCODE cCRE registry, or running gene-set enrichment on peak-associated genes.

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Assess whether a hospitalized adult with diabetes on insulin pump therapy remains a candidate for continued inpatient pump use. Consider triggers such as the clinician asking "Is this patient appropriate to continue insulin pump in hospital?" and evaluate for impaired consciousness, inability to adjust pump settings, critical illness, DKA, or hyperosmolar hyperglycemic state.

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This skill determines whether inpatient diabetic patients meet high-risk criteria for CGM initiation using Table 3 factors such as age ≥65 years, BMI ≤27 kg/m², type 1 diabetes, insulin regimen, and specific clinical conditions. It is triggered by clinician questions like "Should I assess this inpatient for CGM initiation based on hypoglycemia risk?" or "Is this patient a candidate for inpatient CGM?"

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Suggests that clinicians continue CSII in hospitalized patients with type 1 or type 2 diabetes when the institution has clear protocols for evaluating pump candidates and appropriate monitoring and safety procedures. Trigger phrases include: 'Admitted patient on pump, check hospital pump policy' and 'Inpatient with diabetes using pump, verify institutional guidelines'.

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This skill recommends transsphenoidal selective adenomectomy (TSS) by an experienced pituitary surgeon as the optimal treatment for Cushing's disease in pediatric and adult patients. Use when a patient with ACTH-dependent Cushing syndrome is a surgical candidate; triggers include overt Cushing's syndrome, elevated UFC or late-night salivary cortisol, and pituitary MRI showing an adenoma.

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This skill suggests administering a glucocorticoid antagonist (e.g., mifepristone) in patients with Cushing's disease who have diabetes or glucose intolerance and are not surgical candidates or have persistent disease after transsphenoidal surgery. Consider when encountering persistent hypercortisolism after TSS, contraindications to surgery, or comorbid diabetes/glucose intolerance requiring medical control.

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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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Determines whether adrenal venous sampling (AVS) is needed in addition to CT for lateralizing primary aldosteronism before surgery. Trigger phrases include "patient with primary aldosteronism considering surgery", "unilateral adrenal adenoma on CT", "surgical candidate", and "age <35 with hypokalemia and >1‑cm adenoma".

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Cycle-end retrospective converting recurring judgment failures into durable enforcement. Reviews the cycle's friction — repeated user corrections, guard trips, RCA themes, integrate failures — and turns each recurring one into a landmines.md entry, then proposes graduation candidates up the enforcement funnel (landmine → advisory hook → hard gate). Pairs with standup: standup says what shipped and what's next; retrospective says what kept going wrong and how to stop it structurally. Writes only memory entries and a report — graduation proposals are advisory and require the normal seed.md amendment path to become enforcement. Invoke at the end of a release cycle, an epic, or any stretch of work with repeated friction.

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Automate recruiting and hiring workflows in Ashby -- manage candidates, jobs, applications, interviews, and notes through natural language commands.

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Discover prospect companies from a structured OpenClaw search brief, including public search and user-authorized data sources, then output a conservative candidate list ready for lead screening.

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Find the first batch of foreign-trade prospect companies from public web, LinkedIn, and user-authorized data sources such as customs exports, trade show lists, association directories, CRM/Excel files, or historical customer data, then output a conservative, structured candidate list ready for lead screening.

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Take a markdown file of raw material and shape it into an article through a conversational session — drafting candidate openings, growing the piece paragraph by paragraph, arguing about format (lists, tables, callouts, quotes) at each step. Use when the user has a pile of notes, fragments, or a rough draft and wants help turning it into something publishable.

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Expert-level dark matter physics covering observational evidence, candidate particles, detection methods, structure formation, and alternative gravity theories.

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Bootstrap or harden a project's operating model for mixed human and AI delivery teams. Use when starting a repository, adopting an agent harness, defining authority and risk tiers, coordinating parallel agents safely, binding evidence and review to an exact candidate, or correcting fragmented rules that prevent coherent, consistent, complete delivery.

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[Research] Use when starting a web research task — discover, gather, and triage candidate sources on a topic to feed deeper investigation.

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Use when working in the deepseek-harness repo to find non-obvious simplification candidates, write proposed Agent Notes or inline TODO/FIXME/XXX notes, audit or coalesce superseded Agent Notes, or fold worthwhile simplification ideas from another PR; especially for dead, duplicated, speculative, over-built, added-then-removed, or hand-rolled-where-a-dependency-exists surfaces.

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Evidence-grounded AI research workflow for turning supplied economics, finance, management, and social-science papers or structured records into versioned PaperReading artifacts. Use when Codex must ingest text, Markdown, or a text-based PDF; separate source-grounded claims from researcher analysis; bind findings to evidence IDs and locators; review extraction candidates; migrate v0.2 PaperRecord JSON; validate or verify a v0.3 PaperPackage; generate research extensions; export reviewable JSON or Markdown; or safely update a compatible 13-field literature workbook.

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Compare model candidates using weighted metrics and deterministic ranking outputs. Use for benchmark leaderboards and model promotion decisions.

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从配置的热点源（HN / Reddit / YouTube trending / B 站热门 / 等）抓今天的热门话题，去重 + 粗打分 + 写入 candidates.md。**绝大部分人没有候选池——这是让"我没素材"问题在 onboarding 第二步就消失的钥匙**。触发词："抓热点"/"fetch trends"/"今天有什么可做的"/"trending now"/"找选题"。

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Solves complex, open-ended problems using a knockout tournament mechanism. Generates an initial population of diverse candidate answers, pairs them into head-to-head matches, produces a hybrid "child" solution from each pair, and advances the best of the three through a bracket until a winner emerges. Use this skill whenever the user wants to competitively select the best answer from a field of alternatives, asks for a "tournament" or "bracket" style search, wants a faster alternative to full evolutionary search, or uses phrases like: "run a tournament on this", "bracket-style search", "let solutions compete", "knockout search", "find the best answer by elimination", or "which solution wins?". Also trigger when the problem is open-ended and the user wants a clear winner quickly rather than a deep multi-generation refinement.

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Solves complex, open-ended problems using an evolutionary search mechanism inspired by genetic algorithms. Generates a diverse population of candidate answers, scores them against a rubric, then iteratively applies selection, crossover, and mutation to breed progressively better solutions. Use this skill whenever the user wants to explore a solution space deeply, asks for the "best" answer to a subjective or multi-dimensional problem, wants to evaluate competing approaches and distill the strongest, or uses any of these triggers: "evolutionary search", "genetic algorithm", "evolve an answer", "breed solutions", "population-based search", or phrases like "give me multiple approaches and refine the best one". Also trigger when the problem is complex, open-ended, or has no obvious single correct answer and the user wants a high-quality, well-explored result, not just a quick response.

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Research and stress-test open-source project names, from collision checks to launch-ready decisions. Use when the user asks to name or rename a project, compare candidate names, screen GitHub or package namespace risk, verify language or mythology claims, or improve SEO/GEO clarity. Perform live web and registry research, separate brand from category descriptor, classify collisions, and return one evidence-backed recommendation.

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Use when code changes may require documentation updates; maps git diff to candidate docs without auto-editing documentation.

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