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Add an external probabilistic classifier to a decision path without letting it take the path over. Covers finding the externally-graded rows you are already logging, measuring the confidence separation between the overrides it got right and the ones it got wrong, choosing an operating point your data licenses, failing open at the call site, and proving the whole arrangement offline with no API key. Applies to any service returning a score you can order — TypeSafe AI's System One models (Jev) are the worked example. Most of the method transfers to a local model or a second heuristic, with the parts that do not called out where they arise. Use when a rule-based path is wrong often enough to hurt, when someone proposes replacing a heuristic with a model, when a confidence threshold needs a defensible value, or when an oracle already in production has never been graded.

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AI internal coordination using stigmergic signals — managing information freshness in context and memory, decay rates for assumption staleness, and emergent coherent behavior from simple local protocols. Use during complex tasks where multiple sub-tasks must coordinate, when context has grown long and information freshness is uncertain, after context compression when information may have been lost, or when sub-task outputs need to feed into each other cleanly without degradation.

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Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination.

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Catalog and classify materials using standard library systems. Covers descriptive cataloging, subject headings, call number assignment using Dewey Decimal and Library of Congress Classification, MARC record basics, shelf organization, and authority control for consistent access points. Use when organizing a personal, institutional, or community library from scratch, assigning call numbers and subject headings to new acquisitions, reclassifying a collection that has outgrown its original system, or establishing authority control for authors, series, or subjects.

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Achieve distributed agreement without central authority using bee democracy, threshold voting, and quorum sensing. Covers proposal generation, advocacy dynamics, commitment thresholds, deadlock resolution, and consensus quality assessment. Use when a group must decide between options without a designated leader, when centralized decision-making is a bottleneck, when stakeholders have different perspectives to integrate, or when designing automated systems that must reach consensus such as distributed databases or multi-agent AI.

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AI multi-path reasoning coherence using bee democracy — independent evaluation of competing approaches, waggle dance as reasoning-out-loud, quorum sensing for confidence thresholds, and deadlock resolution. Use when forage-solutions has identified multiple valid approaches and a selection must be made, when oscillating between options without committing, when justifying an architecture or tool choice with structured reasoning, or before an irreversible action where the cost of the wrong choice is high.

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Audit project dependencies for version staleness, security vulnerabilities, and compatibility issues. Covers lock file analysis, upgrade path planning, and breaking change assessment. Use before a release to ensure dependencies are current and secure, during periodic maintenance reviews, after receiving a security advisory, when upgrading to a new language version, before submitting to CRAN or npm, or when inheriting a project to assess its dependency health.

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Build sequential (stateful) logic circuits including latches, flip-flops, registers, counters, and finite state machines. Covers SR latch, D and JK flip-flops, binary/BCD/ring counters, and Mealy/Moore FSM design with clock signal and timing analysis. Use when a circuit must remember past inputs, count events, or implement a state-dependent control sequence.

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Parses and merges Claude .jsonl transcripts with debug logs to generate a timeline heuristics report of API limits, context overflows, hook blocks, and tool failures.

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Expert-level Slack platform development using Bolt SDK — build Slack apps with slash commands, interactive components (buttons, modals, shortcuts), home tabs, event subscriptions, workflows, Socket Mode, and Block Kit. Use for building Slack bots, workflow automation, and rich interactive Slack experiences.

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Auto-evolution skill to initialize a new repository with AGENTS.md localized context.

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Fintech engineering expertise — payment processing (Stripe, Plaid), PCI DSS compliance, financial data modeling (double-entry bookkeeping), fraud detection patterns, bank-grade security (encryption, tokenization), open banking APIs, cryptocurrency/blockchain integration, regulatory compliance (KYC/AML), and idempotent financial transaction design. Use for payment systems, banking apps, trading platforms, and fintech infrastructure.

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Docker Compose container orchestration and management. Manage multi-container applications, services, networks, and volumes. Use for local development, testing, and orchestration of containerized applications.

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Validate planned changes against local framework rules and policy guardrails before implementation or creation.

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Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski rule of five, Veber, Oprea, CNS, lead-like, rule of three), structural alert catalogs (PAINS a/b/c, NIBR screening-deck severity, Brenk, BMS, Glaxo, Dundee, ChEMBL common alerts), ZINC-15 percentile complexity metrics (Bertz, SAscore, QED, Whitlock, Barone), chemical-group detection, Lilly demerits, and the medchem query language (MATCHRULE, HASALERT, HASPROP, HASGROUP) for filtering a library at scale. Also trigger on medchem, `import medchem as mc`, RuleFilters, NIBRFilters, CommonAlertsFilters, NamedCatalogs, QueryFilter, PAINS filtering, or structural alerts.

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Protein language models through the EvolutionaryScale `esm` Python SDK. Generate and embed sequences with ESM3 (multimodal sequence, structure and function prompting), extract per-residue and mean-pooled embeddings with ESM C, fold sequences with ESMFold2, and run inference locally or against the Forge and Biohub hosted clients. Use this skill for protein representation learning, variant effect and mutational scanning from likelihoods, sequence generation and inpainting, structure prediction from sequence alone, and embedding features for downstream models. Also trigger on esm, ESM3, ESMC, ESM Cambrian, ESMFold2, `from esm.models`, ESMProtein, GenerationConfig, forge.evolutionaryscale.ai, biohub.ai, or ESM_API_KEY.

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Estimate how likely a protein therapeutic is to provoke an anti-drug antibody response, and locate the sequence regions responsible. Use this skill to tile a sequence into peptides, predict class II MHC presentation across a population-representative allele panel, aggregate predicted binders into a per-region and whole-molecule risk score, compare a candidate against its closest human germline, and decide which liabilities are worth deimmunising. Also trigger on immunogenicity, anti-drug antibody, ADA, T-cell epitope, MHC class II, HLA-DRB1, NetMHCIIpan, NetMHCpan, deimmunisation, tregitope, or population coverage.

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Access a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.

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Query the Precision Medicine Knowledge Graph (PrimeKG) for multiscale biological relationships across genes and proteins, drugs, diseases, phenotypes, pathways, biological processes, exposures and anatomy. Use this skill to search entities by name, pull direct neighbours and their evidence types, summarise the local network around a disease, and find direct or two-hop drug-disease connections for repurposing hypotheses. Also trigger on PrimeKG, kg.csv, Harvard Dataverse knowledge graph, disease_protein, drug_protein, indication and contraindication edges, or network pharmacology over a biomedical knowledge graph.

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Turn a set of structures into absorption, distribution, metabolism, excretion, and toxicity estimates with ADMET-AI, and read them as a developability verdict rather than a table of numbers. Use this skill to run batch prediction over a library, interpret each endpoint against its DrugBank-approved percentile, and flag the liabilities that stop a series — hERG blockade, CYP inhibition, poor Caco-2 permeability, high clearance, and plasma protein binding. Also trigger on ADMET-AI, admet_ai, Chemprop-RDKit, hERG liability, CYP3A4 inhibition, Caco-2, bioavailability prediction, or developability triage.

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Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.

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Ask Kimi a read-only free-form question about the current repository. Use for prose explanations, flow tracing, module comparisons, or conceptual reasoning where Codex should delegate the answer to local kimi-code rather than perform implementation.

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用户面对系统阻塞/瓶颈问题, 需要找到阻塞点并疏通时; 当系统"上实下虚" 或"上虚下实"等方向性阻塞时; 当直接在问题点干预无效, 需要另辟蹊径时。 不适用于: 没有阻塞的问题、可以简单修复的场景、纯资源不足(非阻塞型)的场景。

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Spot-check citations in library files for obvious hallucinations. Resolves DOIs against the DOI registry, validates arXiv IDs, checks the format of journal references. Soft-fails on transient lookup failures rather than blocking. Recommended after kb-ingest and as part of periodic library hygiene.

日本語の概要は準備中です。原文の説明を表示しています。