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cccskills

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概要と使いどころ

Comprehensive health check across CC auto-memory and agent-studio memory systems — detects orphans, duplicates, staleness, and threshold violations

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。

oimiragieo/agent-studio422026年7月14日 更新

Entity and relation tracking skill using MCP memory server patterns and local knowledge graph storage. Build persistent knowledge graphs of entities, relationships, and observations across agent sessions. Covers the MCP memory server (@modelcontextprotocol/server-memory), local JSON-based graphs, and entity-relation querying patterns for long-running agents.

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。

oimiragieo/agent-studio422026年7月14日 更新

Convert files to Markdown using Microsoft's MarkItDown library

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。

oimiragieo/agent-studio422026年7月14日 更新

NativeScript best practices and patterns for mobile applications

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。

oimiragieo/agent-studio422026年7月14日 更新

Scheduled Exa web search monitor. Uses CronCreate to search configured topics every 4 hours via mcp__Exa__web_search_exa, deduplicates URLs via MemoryRecord, and stores summaries for morning briefing integration.

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。

oimiragieo/agent-studio422026年7月14日 更新

Flutter and Dart expert including widgets, state management, and platform integration

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。

oimiragieo/agent-studio422026年7月14日 更新

Estimate per-turn token attribution across 6 categories in Claude Code sessions to show where context budget is spent

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。

oimiragieo/agent-studio422026年7月14日 更新

Expert Electron desktop application development — main/renderer process architecture, IPC communication, native OS APIs (menus, tray, notifications, dialogs), auto-updates, code signing, packaging with electron-builder/forge, security hardening (contextIsolation, sandbox), and performance optimization. Use for building cross-platform desktop apps.

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。

oimiragieo/agent-studio422026年7月14日 更新

Scheduled ArXiv paper monitor. Uses CronCreate to search configured keywords every 6 hours, deduplicates via MemoryRecord, and stores summaries in named memory for morning briefing integration.

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。

oimiragieo/agent-studio422026年7月14日 更新

Atlassian ecosystem integration covering Jira project management, Confluence documentation, Bitbucket source control, and cross-product automation workflows

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。

oimiragieo/agent-studio422026年7月14日 更新

primekg

無料

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.

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。

K-Dense-AI/drug-discovery-agent-skills422026年10月12日 更新

rowan

無料

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.

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。

K-Dense-AI/drug-discovery-agent-skills422026年10月12日 更新

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.

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。

K-Dense-AI/drug-discovery-agent-skills422026年10月12日 更新

depmap

無料

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), RNAi DEMETER2 scores, PRISM compound sensitivity, and gene effect profiles across the cell-line panel. Use for identifying cancer-selective vulnerabilities, separating pan-essential genes from selective ones, finding synthetic lethal interactions, correlating dependency with mutation, expression and copy number, and validating oncology drug targets. Also trigger on DepMap, Chronos gene effect, CRISPRGeneEffect.csv, DEMETER2, PRISM repurposing, co-essentiality, pan-essential, or ACH- cell line identifiers.

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。

K-Dense-AI/drug-discovery-agent-skills422026年10月12日 更新

Run a read-only parallel Kimi review fan-out across many independent targets. Use only for explicit broad fan-out requests where one subagent per target is the point.

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。

linxule/kimi-plugin-cc422026年10月15日 更新

Onboarding workflow for cross-library KB query in a consulting practice. Discovers existing user-scope library registrations, prompts for additions, validates each library, helps activate the relevant ones for the current project, runs a smoke test, and reports a clear "ready" or "issues to fix" verdict. Use --verify-only to skip prompting and just validate existing setup (sub-task 23 of

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。

SteveGJones/ai-first-sdlc-practices412026年10月5日 更新

Policy for the cross-model council: when to hand off to an installed sibling plugin's own slash command (`/codex:*`) versus dispatching our `delegation-runner` (backend: codex|agy|…), which backend to pick, what permission posture to use, and the fan-out/cost discipline that applies regardless of backend — plus the council layer built on that substrate: which play to run, how a cast gets picked from the project roster, budget guardrails, and where project policy/commission config lives. Consult before delegating out to a peer agentic CLI, before choosing between a sibling plugin's command and our runner, before choosing a permission posture, before fanning out more than one external delegation concurrently, or before running a council play (`/…:council-run`).

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。

SteveGJones/ai-first-sdlc-practices412026年10月5日 更新

Dispatch a structured cross-phase review of a phase artefact. MANDATORY for design-spec and test-spec; the gate validator checks for the resulting review record before passing. Recommended for requirements-spec.

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。

SteveGJones/ai-first-sdlc-practices412026年10月5日 更新

Run a Programme phase gate validator (requirements / design / test / code) against docs/specs/<feature-id>/. Block on missing artefact or broken cross-phase reference.

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。

SteveGJones/ai-first-sdlc-practices412026年10月5日 更新

Parse all `# implements:` annotations in source code and emit `library/_code-index.md` as a shelf-index. Also extracts cross-module import edges and writes `library/_dependency-edges.md`. Idempotent — re-running produces byte-identical output if no annotations or imports changed.

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。

SteveGJones/ai-first-sdlc-practices412026年10月5日 更新

This skill should be used when the user wants to build, set up, or operate an AI "second brain" — a persistent memory vault (Obsidian-compatible Markdown) that lets an AI agent resume work without re-explaining context, remembers correction instructions across sessions, and auto-organizes raw material into structured knowledge. Trigger on requests like "build my second brain", "set up an Obsidian vault for AI", "give my AI persistent memory", or "make AI stop forgetting".

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。

fuuuuuuma/ai-second-brain-kit412026年5月31日 更新

Use when an output artifact, template, schema, example, or handoff field must stay aligned across commands, skills, docs, and validators.

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。

rohitg00/agentbrain412026年5月27日 更新

Deep research with cross-verification and source tiering. Use when investigating technologies, comparing tools, fact-checking claims, evaluating architectures, or any task requiring verified information. Triggers on "조사해줘", "리서치", "research", "investigate", "fact-check", "비교 분석", "검증해줘".

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。

TheStack-ai/swing-skills412026年4月30日 更新

Used when the user asks to "create slides", "make a presentation", "build a deck", "design slides", "generate a pitch deck", "create a conference talk", "make a keynote", "presentation design", "slide layout", "slide template", "presentation structure", or mentions slides, presentations, decks, or talks in any context. Also triggers when the user wants to plan the content and visual direction of a presentation before generating it. This is the entry-point orchestrator that drives the full slide creation workflow across both HTML and PPTX formats. Examples: "I need to create slides for my conference talk about AI adoption", "can you turn this markdown into a presentation?", "I have a product demo tomorrow and need visual materials", "convert my existing PowerPoint to interactive HTML slides".

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。

proyecto26/slides-ai-plugin412026年4月13日 更新