「repl」の検索結果

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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Create R-based pictogram glyphs for skill, agent, or team icons in the visualization layer. Covers concept sketching, ggplot2 layer composition using the primitives library, color strategy, registration in the appropriate glyph mapping file and manifest, rendering via the build pipeline, and visual verification of the neon-glow output. Use when a new entity has been added and needs a visual icon for the force-graph visualization, an existing glyph needs replacement, or when batch-creating glyphs for a new domain.

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Set up centralized log aggregation with Loki and Promtail (or ELK stack), including log parsing, label extraction, retention policies, and integration with metrics for correlation. Use when consolidating logs from multiple services into a searchable system, replacing local log files with centralized queryable storage, correlating logs with metrics and traces, implementing structured logging with label extraction, or troubleshooting production incidents requiring cross-service log analysis.

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Execute structural metamorphosis using strangler fig migration, chrysalis phases, and interface preservation. Covers transformation planning, parallel running, progressive cutover, rollback design, and post-metamorphosis stabilization for system architecture evolution. Use when assess-form has classified the system as READY for transformation, when migrating from monolith to microservices, when replacing a core subsystem while dependents continue operating, or when any architectural change must be gradual rather than big-bang.

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Generate and optimise novel small molecules with REINVENT 4 — de novo sampling from a chemical language model, scaffold decoration with LibInvent, fragment linking with LinkInvent, and similarity-constrained analogue generation with Mol2Mol. Use this skill to set up reinforcement-learning or curriculum runs, compose a multi-parameter scoring function from docking scores, predictive models, and physicochemical desirability, and read the resulting sampled sets. Also trigger on REINVENT, LibInvent, LinkInvent, Mol2Mol, scaffold hopping, R-group replacement, linker design, chemical language model, or reinforcement-learning molecule optimisation.

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Use when a local coding agent (Codex, Claude Code, Cursor, or similar) needs to operate Multica through the authenticated `multica` CLI: reading or updating issues, comments, metadata, labels, custom properties, subscribers, projects, agents, squads, runtimes, repos, skills, autopilots, attachments, or workspace state; searching issues; inspecting or cancelling agent runs; replying to a Multica issue from an external agent; creating or triaging issues; checking linked pull requests; or safely handling Multica mention/status side effects without relying on the Multica hosted agent runtime.

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Analyzes research papers (PDF/arXiv URL) and converts them into executable code. Automatically activated upon requests for paper replication, algorithm implementation, or research reproduction. Responds to requests like "Implement this paper", "paper2code", "Convert paper to code".

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Capture reproducible screenshots from the currently booted iOS Simulator and turn them into three App Store marketing cards with validated dimensions and concise copy. Use after a successful Simulator build, during the two-minute proof lane, or when replacing prototype images with real app captures.

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Modern Python idioms for any Python 3.10+ project: PEP 8 style, PEP 484/526 type hints, dataclasses, pathlib, enums, f-strings, structural pattern matching (match/case), context managers, exception handling, and null discipline. Stack-agnostic — referenced by every Python plugin in the marketplace. Use this skill to: - Write strongly-typed code with type hints on every function signature and class attribute. - Replace isinstance chains and magic constants with match/case and enums. - Use dataclasses or NamedTuple for value objects and data containers. - Handle resources safely with context managers and pathlib for all file paths. - Apply PEP 8 naming and structure conventions consistently. Do NOT use this skill for: - Framework-specific idioms (Django ORM, FastAPI routers, Flask blueprints — those live in framework plugin skills). - Packaging and dependency management — see python-foundation:python-tooling. - Testing patterns — see python-foundation:pytest-testing.

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Modern PHP idioms for any PHP project (PHP 8.1+): readonly properties, enums, match expressions, constructor property promotion, typed properties, named arguments, nullsafe operator, first-class callable syntax, strict_types, PSR-12 style, and null discipline. Apply when the project is a PHP 8.1+ project. Stack-agnostic — referenced by every PHP plugin in the marketplace. Use this skill to: - Write strongly-typed, immutable-by-default value objects with readonly properties and enums. - Replace switch ladders and magic constants with match expressions and backed enums. - Cut constructor boilerplate with property promotion and express optionality with typed nullable returns. - Keep code PSR-12 compliant with declare(strict_types=1) in every file. Do NOT use this skill for: - Framework-specific idioms (Eloquent, Doctrine, Symfony services, Laravel facades — those live in framework plugin skills). - Composer / autoloading / dependency management — see php-foundation:composer-tooling. - Testing patterns — see php-foundation:php-testing.

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。

Use when authorized workflow history may contain a repeated process worth extracting and replay-testing. Produces a contradiction-tested workflow mined from authorized history.

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。

Use when addressing review feedback in analyze or reception mode, or handling GitHub PR feedback in autonomous, interactive, or summary mode for a named PR target. Classifies, applies, replies, or summarizes comments.

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Use when replacing a greenfield attempt with a clean pad of verified requirements. Not for rebuilding from primitives: use from-first-principle. Requires a committed, VCS-recoverable attempt.

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Use when asked to audit comments in code files and propose structural replacements or deletions with per-candidate approval. Not for deterministic commented-out-code removal: use deslop.

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Create Codex threads and send messages into Codex desktop-app (GUI) threads, then wait for and read their replies, so Claude can orchestrate Codex agents. Use when the user asks to message, direct, steer, start, check on, or hand work to a Codex thread or agent (often given as a thread ID like 01a10323-9edd-...), or to run Codex as a sub-agent.

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Audit an already completed protected Proto UI publication and reconcile immutable external facts with Version entities, release records, and public projections. Use after publication for registry, tag, GitHub Release, asset, checksum, workflow-head, and deployment evidence. Never republish or replace immutable evidence.

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Release one current Proto UI work-item claim when it expired, became invalid, or the contributor stopped. Use only for the contributor's own recorded claim and only when the exact reversible GitHub mutation is authorized. Do not select replacement work, change readiness, or release another contributor's claim.

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Implement or revise one governed Proto UI Host Capability connecting a semantic Module to a bounded host responsibility. Use when capability identity, portable need, public shape, availability, failure, replacement, cleanup, fidelity, Adapter realization, and evidence are fixed by current authority.

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Executes QA test cases created by $aif-qa in human-guided or automated-agent mode, including reusable browser replay scripts. Use when you need to walk through QA one case at a time, record pass/fail results, or have an agent verify and rerun cases through browser, CLI, API, automated tests, or file/document checks.

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Fix RFDB V2 graph data silently not persisting to disk after analysis. Use when: (1) rfdb-server reports "0 nodes, 0 edges" on restart despite successful analysis, (2) segment directories exist but are empty (no .bin files), (3) manifest_index.json shows total_nodes: 0 despite analysis logging 70k+ nodes, (4) Docker builds produce empty graph databases, (5) --clear flag used before analyze command. Root cause: GraphEngineV2::clear() replaces the store with MultiShardStore::ephemeral() which has path: None, causing all flush operations to write to in-memory buffers only.

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Fix scattered/torn regions in hex-grid simulated annealing layouts that use "competitive flood-fill" (one tile per region per outer iteration). Use when: (1) regions of >20 tiles end up dispersed instead of forming compact blobs, (2) maxDist/sqrt(N) dispersion ratio is 10×+ worse than the ideal compact blob, (3) tiles assigned to one region show up in multiple disconnected fragments across the layout, (4) the visualization has a "trypophobia ring" pattern at the perimeter where some regions spill into a perimeter spiral, (5) an overflow spiral fallback exists in the layout code and frequently kicks in for large regions, (6) bigger regions look worse than smaller ones (small regions stay compact, big ones shred). Root cause: interleaved competitive flood-fill (round-robin one tile at a time across all regions) lets large regions get boxed in by neighbors before they finish growing — the unfilled remainder is dumped into the overflow spiral at the perimeter, far from the seed. Fix: replace with sequential region-by-region BFS — process regions in size-descending order, fully claim each region's N contiguous tiles before moving to the next.

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Build with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, FK replacement code generation, OCC retry patterns, ORM migration (Django/Hibernate/Rails), DDL operations, query plan explainability, SQL compatibility validation, and bulk data loading. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader.

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Use for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.

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。

Search Twitter/X, read replies, find users, monitor accounts, export followers & gate X actions through Xquik. Not affiliated with X Corp.

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。