Product & Planning

holobiomicslab Skill

Use when using Casanovo for de novo peptide sequencing on high-stakes datasets (immunopeptidomics, paleoproteomics, or monoclonal antibody discovery) where missing the correct sequence in the top-1 prediction is costly.

holobiomicslab Skill

Use when you have a collection of tandem mass spectrometry spectra in mzML or similar format and need to prepare them for LDA-based motif discovery.

holobiomicslab Skill

Use when you have LC–MS/MS data processed through MZmine2 or MZmine3 and need to construct a feature quantification table for natural product discovery pipelines (e.g., INVENTA prioritization, GNPS networking, or metabolite annotation).

holobiomicslab Skill

Use when when you have LC-MS data (mzML or netCDF format) and a pre-defined list of target metabolites (m/z, retention time, and identifiers) that you wish to extract and quantify across multiple samples, rather than performing untargeted feature discovery.

holobiomicslab Skill

Use when after Mass2Motif discovery via LDA on preprocessed MS/MS spectra, when you have a set of inferred motifs (fragments and neutral losses with LDA probabilities) and need to assign putative substructure identities rather than retain anonymous motif labels.

holobiomicslab Skill

Use when you have processed LC-MS/MS spectral data (as a .mgf file with feature identifiers) and computed pairwise ms2deepscore similarity scores, and you need to create a 2-D projection suitable for dashboard visualization or high-level pattern discovery without losing similarity structure.

pjt222 Skill

Crear y mantener un backlog de producto o proyecto con elementos priorizados, criterios de aceptación y estimaciones. Cubre la escritura de historias de usuario, la priorización MoSCoW, el refinamiento del backlog, la división de elementos y el seguimiento de estados. Usar al iniciar un nuevo proyecto y convertir el alcance en elementos accionables, durante el refinamiento continuo antes de la planificación del sprint, al repriorizar después de comentarios de interesados o cambios de alcance, o al dividir elementos sobredimensionados en piezas implementables.

holobiomicslab Skill

Use when you have raw MS/MS spectral data in one or more standard mass spectrometry file formats (.mgf, .msp, or .mzML) and need to convert them into a standardized bag-of-fragments representation for unsupervised topic modeling or substructure discovery workflows.

holobiomicslab Skill

Use when after data normalization (Step 7) on the preprocessed feature matrix when you need to identify and flag anomalous samples before statistical testing or biomarker discovery.

holobiomicslab Skill

Use when you have raw MS/MS spectra in one of the supported exchange formats (.mgf, .mzML, or .msp) and need to ingest them into an MS2LDA pipeline for unsupervised motif discovery. This skill is required before any preprocessing, filtering, or ionization-mode-specific handling can occur.

holobiomicslab Skill

Use when when building an automated converter discovery and job enumeration system where converter classes are dynamically loaded from package directories and you need to extract and validate their internal conversion method signatures without prior knowledge of which converters will be available.

holobiomicslab Skill

Use when when you have preprocessed mass spectral data (normalized peak intensities or binned m/z representations) and need to discover latent spectral patterns to enhance neural network predictors without labeled spectral classes.

holobiomicslab Skill

Use when you have raw MS/MS spectral data in standard mass spectrometry formats and need to prepare it for unsupervised substructure discovery via topic modeling.

holobiomicslab Skill

Use when you have raw MS/MS spectra in supported formats (.mgf, .mzML, or .msp) from mixed ionization modes and need to prepare them for downstream topic modeling (LDA) or motif discovery.

holobiomicslab Skill

Use when you have preprocessed MS/MS spectral data (in positive or negative ion mode) and seek to discover recurring fragmentation and neutral-loss patterns that characterize molecular substructures across a dataset.

holobiomicslab Skill

Use when use this strategy when analyzing tandem mass spectrometry data where you expect both unmodified and modified peptide identifications and require high confidence assignments with controlled false discovery rates.

holobiomicslab Skill

Use when you have raw MS/MS spectra in MGF, mzML, or msp format and need to prepare them for mass2motif discovery or topic modeling.

holobiomicslab Skill

Use when when you have high-resolution mass-spectrometry (HRMS) breath data in mzML or mzXML format from multiple subjects or conditions and need to prepare a sample-by-feature intensity matrix for downstream statistical comparison, biomarker discovery, or classification tasks.

pjt222 Skill

優先順位付きアイテム、受け入れ基準、見積もりを含むプロダクトまたはプロジェクトの バックログを作成・管理します。ユーザーストーリーの作成、MoSCoW優先順位付け、 バックロググルーミング、アイテムの分割、ステータス追跡を網羅します。 新しいプロジェクトを開始してスコープを実行可能なアイテムに変換する際、 スプリント計画前の継続的なグルーミング時、ステークホルダーのフィードバックや スコープ変更後の再優先順位付け時、または大きすぎるアイテムを実装可能な 部分に分割する際に使用します。

pjt222 Skill

Plan a multi-stop tour route with waypoint optimization, drive/walk time estimation, and POI discovery along the route using OSM data. Covers geocoding, nearest-neighbor and TSP-based ordering, time/distance matrix calculation, and itinerary generation with points of interest. Use when planning a road trip or walking tour with multiple destinations, optimizing visit order to minimize travel time, discovering sites along a route, or comparing driving versus walking versus public transport options.

pjt222 Skill

Plan a sprint by refining backlog items, defining a sprint goal, calculating team capacity, selecting items, and decomposing them into tasks. Produces a SPRINT-PLAN.md with goal, selected items, task breakdown, and capacity allocation. Use when starting a new sprint in a Scrum or agile project, re-planning after significant scope change, transitioning from ad-hoc work to structured sprint cadence, or after backlog grooming when items are ready for inclusion.

holobiomicslab Skill

Use when when you have aligned and quantified mass spectrometry features from multiple natural extracts (via MZmine2/3), paired with in silico annotation results (ISDB or SIRIUS), and you need to prioritize samples for chemical discovery based on the proportion of unannotated, extract-specific.

holobiomicslab Skill

Use when when performing large-scale untargeted metabolomics annotations where you need to assess the false discovery rate of metabolite identifications but lack sufficient negative control samples or decoy compound databases.

pjt222 Skill

Planificar un sprint refinando elementos del backlog, definiendo un objetivo de sprint, calculando la capacidad del equipo, seleccionando elementos y descomponiéndolos en tareas. Produce un SPRINT-PLAN.md con el objetivo, los elementos seleccionados, el desglose de tareas y la asignación de capacidad. Usar al comenzar un nuevo sprint en un proyecto Scrum o ágil, al replanificar tras un cambio significativo de alcance, al pasar de trabajo ad-hoc a una cadencia de sprint estructurada, o después del refinamiento del backlog cuando los elementos están listos para su inclusión.

pjt222 Skill

Create a new agent definition file following the agent-almanac agent template and registry conventions. Covers persona design, tool selection, skill assignment, model choice, frontmatter schema, required sections, registry integration, and discovery symlink verification. Use when adding a new specialized agent to the library, defining a persona for a Claude Code subagent, or creating a domain-specific assistant with curated skills and tools.

pjt222 Skill

Create a new agent definition file following the agent-almanac agent template and registry conventions. Covers persona design, tool selection, skill assignment, model choice, frontmatter schema, required sections, registry integration, and discovery symlink verification. Use when adding a new specialized agent to the library, defining a persona for a Claude Code subagent, or creating a domain-specific assistant with curated skills and tools.

pjt222 Skill

创建和维护包含优先级条目、验收标准和估算值的产品或项目待办事项列表。 涵盖用户故事编写、MoSCoW 优先级排序、待办事项梳理、条目拆分和状态跟踪。 适合在新项目启动时将范围转化为可操作条目、在冲刺规划前持续进行梳理、 在干系人反馈或范围变更后重新排序，或将过大条目拆分为可实施的部分时使用。

pjt222 Skill

Plan a sprint by refining backlog items, defining a sprint goal, calculating team capacity, selecting items, and decomposing them into tasks. Produces a SPRINT-PLAN.md with goal, selected items, task breakdown, and capacity allocation. Use when starting a new sprint in a Scrum or agile project, re-planning after significant scope change, transitioning from ad-hoc work to structured sprint cadence, or after backlog grooming when items are ready for inclusion.

pjt222 Skill

Apply ant colony optimization and foraging theory to resource search, exploration-exploitation tradeoffs, and distributed discovery. Covers scout deployment, trail reinforcement, diminishing returns detection, and adaptive foraging strategy selection. Use when searching a large solution space where brute-force enumeration is impractical, balancing investment between exploring new approaches and deepening known good ones, optimizing resource allocation across uncertain opportunities, or diagnosing premature convergence on local optima.

pjt222 Skill

Plan a sprint by refining backlog items, defining a sprint goal, calculating team capacity, selecting items, and decomposing them into tasks. Produces a SPRINT-PLAN.md with goal, selected items, task breakdown, and capacity allocation. Use when starting a new sprint in a Scrum or agile project, re-planning after significant scope change, transitioning from ad-hoc work to structured sprint cadence, or after backlog grooming when items are ready for inclusion.

pjt222 Skill

Apply ant colony optimization and foraging theory to resource search, exploration-exploitation tradeoffs, and distributed discovery. Covers scout deployment, trail reinforcement, diminishing returns detection, and adaptive foraging strategy selection. Use when searching a large solution space where brute-force enumeration is impractical, balancing investment between exploring new approaches and deepening known good ones, optimizing resource allocation across uncertain opportunities, or diagnosing premature convergence on local optima.

pjt222 Skill

Create a new agent definition file following the agent-almanac agent template and registry conventions. Covers persona design, tool selection, skill assignment, model choice, frontmatter schema, required sections, registry integration, and discovery symlink verification. Use when adding a new specialized agent to the library, defining a persona for a Claude Code subagent, or creating a domain-specific assistant with curated skills and tools.

pjt222 Skill

Configure reverse proxy patterns across multiple tools including Nginx, Traefik, and ShinyProxy. Covers WebSocket proxying, path-based and host-based routing, SSL termination, and Docker label auto-discovery. Use when routing multiple services behind a single entry point, proxying WebSocket connections (Shiny, Socket.IO), auto-discovering Docker services with Traefik labels, or adding SSL termination to services that don't handle TLS natively.

pjt222 Skill

Create and maintain a product or project backlog with prioritized items, acceptance criteria, and estimates. Covers user story writing, MoSCoW prioritization, backlog grooming, item splitting, and status tracking. Use when starting a new project and converting scope into actionable items, during ongoing grooming before sprint planning, re-prioritizing after stakeholder feedback or scope changes, or splitting oversized items into implementable pieces.

pjt222 Skill

Create and maintain a product or project backlog with prioritized items, acceptance criteria, and estimates. Covers user story writing, MoSCoW prioritization, backlog grooming, item splitting, and status tracking. Use when starting a new project and converting scope into actionable items, during ongoing grooming before sprint planning, re-prioritizing after stakeholder feedback or scope changes, or splitting oversized items into implementable pieces.

pjt222 Skill

Plan a multi-stop tour route with waypoint optimization, drive/walk time estimation, and POI discovery along the route using OSM data. Covers geocoding, nearest-neighbor and TSP-based ordering, time/distance matrix calculation, and itinerary generation with points of interest. Use when planning a road trip or walking tour with multiple destinations, optimizing visit order to minimize travel time, discovering sites along a route, or comparing driving versus walking versus public transport options.