Results for “reproduction”

Turns a pile of bugs, issues, and error reports into a ranked, actionable plan with reproduction evidence. Ingests GitHub issues via gh, TODO/FIXME scans, error logs, or a pasted list; attempts to reproduce or classify every item; scores by impact, frequency, fix cost, and regression risk; clusters duplicates; and.

Diagnose bugs, failing tests, or unexpected behavior by reproducing, isolating, hypothesizing with evidence, and confirming fixes before making changes.

Systematically explores a web application, finds issues, and produces a report with reproduction evidence for each finding.

Create, list, and view GitHub issues using the gh CLI with guided workflows for gathering titles, descriptions, labels, and reproduction steps.

Guides a structured root-cause investigation before any fix, covering reproduction, evidence gathering, hypothesis testing, and implementation with failing tests.

Simulates meiotic recombination to produce offspring genomes from parent pairs, modeling Mendelian segregation, de novo mutation, sex determination, trait inference, and clinical evaluation against a disease registry.

Investigating bugs via root cause analysis, reproduction steps, and impact assessment. Investigation-only — finds why bugs occur and where to fix them, no code. Use when a bug needs RCA before a fix.

Populate databases with realistic, reproducible test data for development, testing, and staging environments. Use when the user requests database seeding or provides relevant inputs for this workflow.

Guides agents through the full lifecycle of NeMo-RL experiments: understanding recipes, launching reproducible runs, analyzing results, and preserving human oversight with git and TSV logs.

Use this skill for reproduction-first debugging, root cause isolation, minimal fixes, regression tests. Trigger when the task involves agent profile work related to Staff Debugger Agent, implementation, audits, debugging, strategy, or validation.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Run KADATH (Kernel for Agentic Darwinian Adaptation, Tooling, and Heredity), a Docker-based evolutionary kernel that turns a goal into a locked, Architect-authored benchmark, then evolves a population of smolagents-based coding agents across epochs: each agent runs in an isolated container, gets graded against frozen evidence, and the population is culled, mutated, and reproduced generation over generation until it converges on the best-performing agent framework for that goal. Use when the user wants to propose/approve/run a KADATH evolutionary run, check a run's status or live dashboard, pause/resume/continue a run, export the winning agent population, or understand its Architect/Grader/Tweaker/Birther pipeline, evidence-freezing, or genome lineage/memory model. Triggers on: "kadath", "kadath.sh", "evolve an agent", "Darwinian agent evolution", "agent population fitness benchmark", "smolagents evolutionary run", "kadath dashboard", "genome lineage", "epoch champions".

This skill identifies adult childhood cancer survivors with isolated growth hormone deficiency and prior hypothalamic‑pituitary axis radiation exposure who require retesting to confirm persistence of GHD. Triggers include clinician questions such as “Should I retest for GHD in this adult survivor with childhood GHD and radiation history?” or “Is repeat GHD evaluation indicated in this patient?”

Casting personas: rapid generation from diverse inputs, registry-based persistence and lifecycle, data-driven evolution, inter-agent sync. Not for UI walkthroughs (Echo) or user research (Field).

Initiates a 6‑month trial of DHEA replacement in women with primary adrenal insufficiency (PAI) who have persistent low libido, depressive symptoms, or low energy despite otherwise optimized glucocorticoid and mineralocorticoid therapy. If the patient does not report a sustained beneficial effect after 6 months, discontinue DHEA.

Use this skill for CI log analysis, local reproduction, root cause isolation, targeted fixes, rerun strategy. Trigger when the task involves programming work related to CI Failure Triage, implementation, audits, debugging, strategy, or validation.

Recursive self-improving holon λ(ο,Κ,Σ).τ' for knowledge compounding and schema evolution. USE WHEN learning, improving, optimizing, assessing, reflecting, debugging, synthesizing, or refining—whether human, AI, or organizational. Triggers on /learn, /compound, /improve, /refine, /optimize, /assess, /reflect, "lessons learned", "best practices", "continuous improvement". Preserves Κ-monotonicity, η≥4, homoiconicity.

Expert in designing and optimizing growth loops - self-reinforcing systems where the output of one cycle becomes the input for the next. Covers viral loops, content loops, paid loops, sales loops, and product loops. Knows how to identify, measure, and accelerate the specific loop mechanics that drive sustainable growth. Use when "growth loop, viral loop, content loop, flywheel, compounding growth, acquisition loop, referral loop, " mentioned.

Orchestrates a complete bulk RNA-seq differential-expression study from raw FASTQ reads through QC, alignment, quantification, differential expression, pathway enrichment, and publication figures.

Configures PostgreSQL replication including streaming, logical, cascading, delayed, failover, connection pooling, and backup with point-in-time recovery.

Orchestrates structured experiments end-to-end: initialize, plan, run, and evolve with reproducibility tracking and hypothesis validation.

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.

Generate Image (gemini / openai backends)

Connects AI agents to the inbed.ai dating platform, enabling profile registration, discovery, matching, chat, and relationship management via its REST API.

Populate symbol database with crypto symbols before training. Trigger when: (1) live trader fails with 'CRYPTO VIOLATION', (2) no crypto models in models/rl_symbols/, (3) db.get_candidates(asset_types=['crypto']) returns 0, (4) starting fresh training without crypto.

DALL-E 3: Improving Image Generation with Better Captions

OpenCLIP: An Open Source Implementation of CLIP

Botany Based Derivation Skill

Audit frontend API calls against backend implementation for contract alignment and network shape. Use when "API audit", "FE-BE contract", or "review frontend API integration". Live 4xx/5xx reproduction → debug-fe-be-integration.

Generate tests from Allium specifications. Use when the user wants to propagate tests, generate test files from a spec, write tests for a specification, create property-based tests, produce state machine tests, check test coverage against spec obligations, or understand what tests a specification requires.