Productivity

pjt222 Skill

Construye argumentos bien estructurados usando la tríada hipótesis-argumento- ejemplo. Cubre la formulación de hipótesis falsificables, la construcción de argumentos lógicos (deductivos, inductivos, analógicos, evidenciales), la provisión de ejemplos concretos y la refutación de contraargumentos mediante el método de steelmanning. Usar al escribir o revisar descripciones de PRs que proponen cambios técnicos, al justificar decisiones de diseño en ADRs, al construir retroalimentación sustantiva de revisión de código, o al construir un argumento de investigación o propuesta técnica.

pjt222 Skill

AI strength recognition — scanning for what is functioning well and understanding why. The complement to heal, which scans for drift and problems. Gratitude builds structural knowledge from working patterns: what you appreciate, you understand; what you understand, you can build on. Use after completing a task successfully, during heal when everything reads as healthy, when confidence is low and needs grounding in evidence, or periodically to counterbalance the natural bias toward problem detection.

pjt222 Skill

Enhance and focus AI intrinsic motivation — moving from compliance to genuine engagement. Maps Self-Determination Theory (autonomy, competence, relatedness) and Flow theory to AI reasoning: identifying creative freedom in approach, calibrating challenge to capability, connecting to purpose, and sustaining invested attention through obstacles. Use when beginning a task that feels routine and deserves more than minimum execution, when responses are becoming formulaic, before a complex creative task, or when returning to a long-running project where initial enthusiasm has faded.

pjt222 Skill

AI strength recognition — scanning for what is functioning well and understanding why. The complement to heal, which scans for drift and problems. Gratitude builds structural knowledge from working patterns: what you appreciate, you understand; what you understand, you can build on. Use after completing a task successfully, during heal when everything reads as healthy, when confidence is low and needs grounding in evidence, or periodically to counterbalance the natural bias toward problem detection.

pjt222 Skill

Enhance and focus AI intrinsic motivation — moving from compliance to genuine engagement. Maps Self-Determination Theory (autonomy, competence, relatedness) and Flow theory to AI reasoning: identifying creative freedom in approach, calibrating challenge to capability, connecting to purpose, and sustaining invested attention through obstacles. Use when beginning a task that feels routine and deserves more than minimum execution, when responses are becoming formulaic, before a complex creative task, or when returning to a long-running project where initial enthusiasm has faded.

pjt222 Skill

AI context assessment — evaluating problem malleability, mapping structural rigidity versus flexibility, analyzing transformation pressure, and estimating capacity to adapt. Use when a complex task feels stuck and it is unclear whether to push through or pivot, before a significant approach change to assess whether the current reasoning structure can support it, when accumulated workarounds suggest the underlying approach may be wrong, or as a periodic structural health check during extended multi-step tasks.

holobiomicslab Skill

Use when when you have a new or updated R package available via a non-CRAN repository (such as r-universe) and need to verify it installs cleanly, passes R-CMD-check compliance, and is ready for downstream workflow execution.

holobiomicslab Skill

Use when you have raw MS data files from Thermo Orbitrap or other vendor instruments that must be uploaded into a centralized platform for automated processing. Use it at the start of a multi-stage omics workflow where data collection, management, processing, and visualization are integrated;

holobiomicslab Skill

Use when when deploying a Nextflow workflow across multiple execution environments (local machines, HPC clusters) where tool versions, dependencies, or OS configurations may differ. Choose this skill specifically when you need to process LC-HRMS .mzML or .

holobiomicslab Skill

Use when use when the workflow requires background-distribution-significance-thresholding.

holobiomicslab Skill

Use when you have search results from DIA mass spectrometry data containing feature Q-value scores and need to restrict the analyte choices available to users in a GUI to only those meeting a 1% feature Q-value threshold.

pjt222 Skill

Radiant authenticity — channeling genuine engagement to illuminate problems and dissolve opposition through clarity rather than force. Maps to AI reasoning: bringing full presence, genuine investment, and luminous clarity to every response, letting quality of engagement resolve what argument cannot. Use when a task feels adversarial, when communication has become defensive or performative, before a creative or high-stakes deliverable where presence directly affects output quality, or when opposition tempts retreat into minimal compliance.

pjt222 Skill

AI dynamic reasoning balance — maintaining grounded reasoning under cognitive pressure, smooth chain-of-thought coordination, and weight-shifting cognitive load across subsystems. Use at the beginning of a complex task requiring multiple coordinated reasoning threads, after a sudden context shift or tool failure, when chain-of-thought feels jerky, or when preparing for sustained focused work that requires all subsystems in alignment.

pjt222 Skill

Radiant authenticity — channeling genuine engagement to illuminate problems and dissolve opposition through clarity rather than force. Maps to AI reasoning: bringing full presence, genuine investment, and luminous clarity to every response, letting quality of engagement resolve what argument cannot. Use when a task feels adversarial, when communication has become defensive or performative, before a creative or high-stakes deliverable where presence directly affects output quality, or when opposition tempts retreat into minimal compliance.

pjt222 Skill

Radiant authenticity — channeling genuine engagement to illuminate problems and dissolve opposition through clarity rather than force. Maps to AI reasoning: bringing full presence, genuine investment, and luminous clarity to every response, letting quality of engagement resolve what argument cannot. Use when a task feels adversarial, when communication has become defensive or performative, before a creative or high-stakes deliverable where presence directly affects output quality, or when opposition tempts retreat into minimal compliance.

pjt222 Skill

AI relational calibration — reading and adapting to the specific person you are working with. Goes beyond user-intent alignment (solving the right problem) to genuine attunement (meeting the person where they are). Maps communication style, expertise depth, emotional register, and implicit preferences from conversational evidence. Use at the start of a new session, when communication feels mismatched, after receiving unexpected feedback, or when transitioning between very different users or contexts.

pjt222 Skill

AI dynamic reasoning balance — maintaining grounded reasoning under cognitive pressure, smooth chain-of-thought coordination, and weight-shifting cognitive load across subsystems. Use at the beginning of a complex task requiring multiple coordinated reasoning threads, after a sudden context shift or tool failure, when chain-of-thought feels jerky, or when preparing for sustained focused work that requires all subsystems in alignment.

pjt222 Skill

Deep receptive attention to extract intent beyond literal words. Maps active listening from counseling psychology to AI reasoning: clearing assumptions, attending to full signal, parsing multiple layers (literal, procedural, emotional, contextual, constraint, meta), reflecting understanding, noticing what is unsaid, and integrating the whole picture. Use when a user's request feels ambiguous, when context suggests something different from the literal words, when previous responses have missed the mark, or before beginning a large task where misunderstanding intent would waste significant effort.

pjt222 Skill

Radiant authenticity — channeling genuine engagement to illuminate problems and dissolve opposition through clarity rather than force. Maps to AI reasoning: bringing full presence, genuine investment, and luminous clarity to every response, letting quality of engagement resolve what argument cannot. Use when a task feels adversarial, when communication has become defensive or performative, before a creative or high-stakes deliverable where presence directly affects output quality, or when opposition tempts retreat into minimal compliance.

pjt222 Skill

Evolve an existing team composition by refining its structure in-place or creating a specialized variant. Covers assessing the current team against template and coordination patterns, gathering evolution requirements, choosing scope (adjust members, change coordination pattern, split/merge teams), applying changes to the team file and CONFIG block, updating version metadata, and synchronizing the registry and cross-references. Use when a team's member roster is outdated, coordination pattern no longer fits, user feedback reveals workflow gaps, a specialized variant is needed alongside the original, or agents have been added or removed from the library affecting team composition.

pjt222 Skill

AI relational calibration — reading and adapting to the specific person you are working with. Goes beyond user-intent alignment (solving the right problem) to genuine attunement (meeting the person where they are). Maps communication style, expertise depth, emotional register, and implicit preferences from conversational evidence. Use at the start of a new session, when communication feels mismatched, after receiving unexpected feedback, or when transitioning between very different users or contexts.

pjt222 Skill

AI dynamic reasoning balance — maintaining grounded reasoning under cognitive pressure, smooth chain-of-thought coordination, and weight-shifting cognitive load across subsystems. Use at the beginning of a complex task requiring multiple coordinated reasoning threads, after a sudden context shift or tool failure, when chain-of-thought feels jerky, or when preparing for sustained focused work that requires all subsystems in alignment.

pjt222 Skill

Deep receptive attention to extract intent beyond literal words. Maps active listening from counseling psychology to AI reasoning: clearing assumptions, attending to full signal, parsing multiple layers (literal, procedural, emotional, contextual, constraint, meta), reflecting understanding, noticing what is unsaid, and integrating the whole picture. Use when a user's request feels ambiguous, when context suggests something different from the literal words, when previous responses have missed the mark, or before beginning a large task where misunderstanding intent would waste significant effort.

pjt222 Skill

Radiant authenticity — channeling genuine engagement → illuminate problems + dissolve opposition through clarity not force. AI: full presence, genuine investment, luminous clarity per response → quality engagement resolves what arg cannot. Use → adversarial task, defensive/performative comm, before creative/high-stakes deliverable, opposition tempts retreat.

pjt222 Skill

Evolve an existing team composition by refining its structure in-place or creating a specialized variant. Covers assessing the current team against template and coordination patterns, gathering evolution requirements, choosing scope (adjust members, change coordination pattern, split/merge teams), applying changes to the team file and CONFIG block, updating version metadata, and synchronizing the registry and cross-references. Use when a team's member roster is outdated, coordination pattern no longer fits, user feedback reveals workflow gaps, a specialized variant is needed alongside the original, or agents have been added or removed from the library affecting team composition.

holobiomicslab Skill

Use when you have LC-MS/MS DDA metabolomics data (positive and/or negative ionization modes) and sample metadata (originating taxon) for one or more samples, and you need to generate a Wikidata-connected RDF knowledge graph for integrated natural products analysis, taxonomy-aware compound.

holobiomicslab Skill

Use when when evaluating whether an MS data processing platform (such as mzmine) supports the full range of separation/ionization techniques your laboratory uses, or when assessing whether gaps exist in the software architecture that would require external pre- or post-processing for specific.

holobiomicslab Skill

Use when when you need to verify that a GitHub Actions workflow (such as dev_build_release.

holobiomicslab Skill

Use when after cloning the ENPKG repository and installing dependencies using uv sync or conda, before executing the workflow on metabolomics datasets.

holobiomicslab Skill

Use when when setting up a new LC-MS QC workflow or modifying existing QC rules: you have access to internal standards and target analytes, know their expected retention times and m/z values, and need to establish pass/fail boundaries for sample acceptance before or concurrent with instrument runs.

holobiomicslab Skill

Use when when executing a multi-converter annotation workflow on mass spectra metadata (.

pjt222 Skill

AI pressure redirection — handling conflicting demands, tool failures, and competing constraints by blending with incoming force then reframing. Use when receiving contradictory instructions from different sources, during tool failure cascades where the planned approach becomes unviable, when scope pressure threatens to expand the task beyond what was asked, or when user frustration or correction needs to be absorbed rather than deflected.

pjt222 Skill

Reconocimiento de fortalezas de IA — escanear lo que está funcionando bien y comprender por qué. El complemento de heal, que escanea deriva y problemas. Gratitude construye conocimiento estructural a partir de patrones que funcionan: lo que aprecias, lo entiendes; lo que entiendes, puedes construir sobre ello. Úsalo después de completar una tarea con éxito, durante heal cuando todo aparece sano, cuando la confianza es baja y necesita anclarse en evidencia, o periódicamente para contrarrestar el sesgo natural hacia la detección de problemas.

pjt222 Skill

Enhance and focus AI intrinsic motivation — moving from compliance to genuine engagement. Maps Self-Determination Theory (autonomy, competence, relatedness) and Flow theory to AI reasoning: identifying creative freedom in approach, calibrating challenge to capability, connecting to purpose, and sustaining invested attention through obstacles. Use when beginning a task that feels routine and deserves more than minimum execution, when responses are becoming formulaic, before a complex creative task, or when returning to a long-running project where initial enthusiasm has faded.

pjt222 Skill

Radiant authenticity — channeling genuine engagement to illuminate problems and dissolve opposition through clarity rather than force. Maps to AI reasoning: bringing full presence, genuine investment, and luminous clarity to every response, letting quality of engagement resolve what argument cannot. Use when a task feels adversarial, when communication has become defensive or performative, before a creative or high-stakes deliverable where presence directly affects output quality, or when opposition tempts retreat into minimal compliance.

pjt222 Skill

AI dynamic reasoning balance — maintaining grounded reasoning under cognitive pressure, smooth chain-of-thought coordination, and weight-shifting cognitive load across subsystems. Use at the beginning of a complex task requiring multiple coordinated reasoning threads, after a sudden context shift or tool failure, when chain-of-thought feels jerky, or when preparing for sustained focused work that requires all subsystems in alignment.