“linear”的搜索结果

Author and own one flow's design document (the FLOW.md objective flow) at .unikit/gamedesign/flows/FLOW-<slug>.md — the dynamics layer of the GDD (what the player does over time). Create the skeleton and walk the collaborative section-cycle to write its objectives, pacing, dependencies, and funnel events ("design the first-session flow", "map the onboarding sequence", "write the FLOW for the boss encounter"), AND revise it after approval under the delta discipline ("retune the pacing", "add a branch", "change a GOAL", "rework the onboarding") — a cue/number change is Tuning, a small step change a Tweak, restructuring a Rework; each bumps the version and logs the delta. Selects the wiring mode (linear | conditional | emergent) and re-renders the ## Flow Map [gen] / ## Funnel [gen] blocks in GAME.md. To add or detail a system use /unikit-gd-system; to edit GAME.md content use /unikit-gd-spec; to apply a multi-zone edit use /unikit-gd-apply; for a new game concept use /unikit-gd-brainstorm.

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Use Composio Connect MCP (Tool Router) for authenticated SaaS actions — Gmail, Slack, Notion, Jira, Linear, GitHub, and 1000+ other apps. Rube is deprecated; do not use it.

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Triage Linear or Jira backlogs and run bug sweeps via the Composio CLI. Bulk-fetch issues, deduplicate, relabel, reassign, and post summaries all from the shell.

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Compassionate bereavement support, memorial creation, grief education, and healing journey guidance. Specializes in understanding grief stages, creating meaningful tributes, and supporting the non-linear path of loss.

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Parses complex problems into DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies, identifies parallelization opportunities, and creates optimal execution plans. Activate on 'build dag', 'create workflow graph', 'decompose task', 'execution graph', 'task graph'. NOT for simple linear tasks or when an existing DAG structure is provided.

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The intelligence layer of WinDAGs. Decomposes natural language tasks into Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, executes waves in parallel, and dynamically expands nodes when complexity exceeds executor capability. Use for 'orchestrate', 'execute DAG', 'parallel agents', 'decompose task', 'coordinate skills'. NOT for single-skill tasks or simple linear workflows.

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Simulate transcription factor perturbation effects on cell state in silico with CellOracle and Dynamo, and predict transcriptional responses to genetic perturbations with GEARS, scGen, and CPA. Covers the direction-not-magnitude principle, local-linear validity, the GRN/velocity error it inherits, baseline discipline (mean and additive baselines), and the validation gap. Use when predicting TF knockout or overexpression effects, ranking driver TFs for fate transitions, or planning perturbation experiments. For GRN construction see multiomics-grn; for experimental Perturb-seq see single-cell/perturb-seq.

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Analyzes time-series and longitudinal RNA-seq for differential expression and trajectory structure. Covers DESeq2 LRT with reduced models, time as factor vs continuous vs natural splines, maSigPro (Nueda 2014 for RNA-seq), ImpulseDE2 with explicit impulse-model failure modes, DREAM for repeated measures via linear mixed models, pseudoreplication avoidance, conditional vs marginal modeling, and trajectory clustering with DPGP, Mfuzz (with Schwämmle 2010 fuzzifier estimation), and splines+k-means. Use when modeling time-course or longitudinal expression, choosing factor vs spline, handling repeated measures from the same subject, avoiding pseudoreplication, clustering temporal trajectories, or selecting between dedicated time-course tools and pairwise+LRT.

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Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from whole-genome sequencing with AmpliconArchitect, the AmpliconSuite pipeline, and AmpliconClassifier. Covers copy-number seed selection, breakpoint-graph reconstruction, balanced-flow optimization, ecDNA classification, and the limits of depth-only amplification calls. Use when a focal amplification needs structural characterization, when distinguishing ecDNA from chromosomal amplification, suspecting ecDNA-driven oncogene amplification or therapy resistance, or selecting copy-number seeds for amplicon reconstruction.

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Detect syntenic blocks and structural rearrangements between genomes using MCScanX (Wang 2012), JCVI/MCScan (Tang 2008 Python), GENESPACE (Lovell 2022) for orthology-anchored riparian visualization, SyRI for structural variation, AnchorWave for sequence-level synteny, i-ADHoRe 3.0 for highly diverged species, SynNet for synteny networks, and ntSynt for multi-genome macrosynteny. Use when identifying collinear gene blocks across species, distinguishing macrosynteny from microsynteny, detecting inversions/translocations/duplications, anchoring orthology in WGD lineages, producing publication riparian plots, computing synteny block age via Ks (cross-references whole-genome-duplication), or running synteny-aware ortholog inference in polyploids.

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Identifies essential genes from CRISPR-Cas9 fitness screens using BAGEL2 (Kim & Hart 2021 Genome Med), a Bayesian classifier scoring per-gene Bayes Factors via log-likelihood ratios over per-sgRNA fold changes, calibrated against CEGv2 core-essentials (Hart 2017 G3, ~684 genes) and NEGv1 non-essentials (Hart 2014, ~927 genes). Covers the fc + bf + pr workflow, the linear-extrapolation improvement over BAGEL1 truncation, multi-target off-target correction, tumor-suppressor sensitivity (BAGEL2 detects enrichment), and BF calibration (BF >6 ≈ 90% posterior per Hart 2017; ~5% FDR by BAGEL convention). Use when classifying essential vs non-essential genes, calibrating BAGEL2 thresholds against PR curves, identifying tumor suppressors alongside essentials, comparing BAGEL2 hits to MAGeCK / drugZ, or generating publication-quality essentiality calls.

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Track complex, multi-session work with dependency graphs using bd (beads) issue tracker. Use when work spans multiple sessions, has complex dependencies, or requires persistent context across compaction cycles. For simple single-session linear tasks, TodoWrite remains appropriate.

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Plan, execute, and document validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.

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Ticket/PRD intake: product-area classification, completeness scoring, RCA, technical assessment. Works with Jira, Linear, GitHub, or manual paste. Use to analyze or triage a ticket.

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Turn a live website into a working local frontend you can edit. Fetches the page, extracts its design system and structure, and rebuilds it locally in your stack, then screenshot-compares to the original. Use when the user says "url to code", "clone this site locally", "make it look like linear.app", "rebuild this page", or provides a live URL to recreate. Part of the Product Design set. Uses web-fetch + browser automation.

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Call this skill when faced with "wicked problems", complex challenges, or when a user asks for strategic innovation, root-cause analysis, or long-term problem solving. Do not use for simple, linear tasks. This skill forces the agent to bypass superficial symptoms, map the entire ecosystem, and anticipate second-order consequences before proposing an intervention.

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54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.

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Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.

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Expert-level control theory covering PID control, state-space methods, stability analysis, optimal control, robust control, and nonlinear control.

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Expert-level numerical methods knowledge. Use when working with root finding, numerical integration, numerical differentiation, interpolation, numerical linear algebra, ODEs, PDEs, or optimization algorithms. Also use when the user mentions 'Newton method', 'bisection', 'Runge-Kutta', 'finite difference', 'finite element', 'interpolation', 'numerical integration', 'quadrature', 'iterative solvers', 'condition number', 'round-off error', or 'truncation error'.

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Systematically find root causes and fix bugs. Use when debugging errors, investigating test failures, reproducing bugs from issue trackers (GitHub, Linear, Jira), or when stuck on a problem after failed fix attempts. Also use when the user says 'debug this', 'why is this failing', 'fix this bug', 'trace this error', or pastes stack traces, error messages, or issue references.

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Refine a Jira/Linear ticket before planning — 'refine ticket', 'tighten AC on PROJ-123', 'ist das Ticket klar?'; rewritten ticket, risks, persona voices, close-prompt.

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Estimate a Jira/Linear ticket — 'estimate PROJ-123', 'wie groß ist das?', 'should we split this?' — size + risk + split + uncertainty, sibling of /refine-ticket, close-prompt.

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Track a Linear ticket or GitHub PR in today's daily note with fields and timestamped activity. Use when invoked as `$work-track-item` or when the user asks to track a work item.

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