Turn a short natural-language request into a bounded work contract (intent, scope, acceptance, initial queue) without asking for code or architecture review.
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。
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概要と使いどころ
Turn a short natural-language request into a bounded work contract (intent, scope, acceptance, initial queue) without asking for code or architecture review.
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。
GitHub Pull Request creation specialist. Analyzes user requirements to create PRs with structured titles and bodies matching the user's query language. Handles git change analysis, PR draft creation, user confirmation, and final PR creation via gh CLI.
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 recording, tallying, or triaging stochastic review findings — the append-only JSONL ledger where Tier 2 (advisory, unevidenced) reviewer output goes instead of blocking language. Triggers on "log this finding", "ledger add", "tally the findings", "triage findings", "is this finding recurring", "retire this noise", or whenever a reviewer produces an unevidenced concern that should be measured for recurrence rather than chased. For the review itself see code-review-and-quality or skill-library-review; for verifying formal claims with deterministic evidence see adversarial-claims-reviewer.
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。
Scan projects for credential leaks, secrets in code, insecure patterns, LLM API key exposure, PII leakage to external AI services, and .env/.gitignore misconfigurations. Especially useful for data and API integrations, regardless of implementation language.
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Draft the QA scope and plain-language Given/When/Then test scenarios for a Jira ticket, built from the full ticket, the decisions made in its comments, and the actual code change read commit by commit (open PR, the ticket's merged PR, the branch against its base, or a named commit range). Saves a Markdown draft under docs/, iterates with the user, then posts it to the ticket as a new Jira comment only after explicit approval. Use on "QA scope for PROJ-123", "what should QA test", "write test scenarios for QA", "hand this ticket to QA", "prep the QA handoff", "gherkin scenarios for this ticket", or when a branch is ready for manual testing — even when the user only names the ticket or says "this branch".
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。
Write or audit technical text against ASD-STE100 Simplified Technical English so a tired, non-native reader understands it on the first pass: 20-word procedural and 25-word descriptive sentence limits, imperative steps, condition before command, one word for one meaning, and only the approved modals can/will/must. Use for READMEs, runbooks, procedures, error messages, release notes, incident reports, API guides, UI copy, and agent instructions. Trigger on: "STE", "Simplified Technical English", "ASD-STE100", "controlled language", "plain English", "make this clearer", "write for non-native readers", "prep this for translation", "cut the fluff", or any request to check text for compliance. Prefer this over general copy-editing whenever the text instructs, documents, or warns.
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。
Enterprise-grade code review agent. Reviews PRs, diffs, or code files for security vulnerabilities, performance issues, error handling gaps, architecture smells, and test coverage. Works with any language, any repo, no dependencies required.
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。
Manage Google Ads & Meta (Facebook) Ads from your AI coding tool. 99 MCP tools for auditing, creating, and optimizing ad accounts using natural language.
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Adspirer — AI-powered advertising and performance marketing agent. Manage Google Ads, Meta Ads (Facebook & Instagram), LinkedIn Ads, and TikTok Ads via natural language. 100+ tools for paid media campaign creation, live performance analysis, PPC keyword research with real CPC data, budget optimization, ad creative management, and cross-platform reporting. Create Search, PMax, display, image, video, and carousel campaigns. Analyze wasted ad spend, research keywords, optimize bids and ROAS, automate monitoring, and track CPA across channels. Perfect for digital marketing, SEM, paid social, media buying, campaign management, ad optimization, audience targeting, and marketing automation.
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Run natural-language data query workflows for Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads, Amazon Ads, and Shopify Ads reports.
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。
Automate advertising campaigns with AI. Create ads, buy media, manage ad budgets, discover ad inventory, run display ads, video ads, CTV campaigns, and optimize ad performance. Perfect for marketing automation, programmatic advertising, media buying, ad management, campaign optimization, creative management, and performance tracking. Launch Facebook ads, Google ads, display advertising, video marketing, and multi-channel campaigns using natural language. Supports ad targeting, audience segmentation, ROI tracking, and automated bidding.
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。
Provides Speech-to-Text (STT) and text Translation using the Addis Assistant API (api.addisassistant.com). Use when the user needs to convert an audio file to text (specifically Amharic), or translate text between languages (e.g., Amharic to English). Requires 'x-api-key'.
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。
Verify and write proofs using the Acorn theorem prover for mathematical and cryptographic formalization. Use when working with Acorn proof files (.ac), verifying theorems, formalizing mathematical or cryptographic protocols, or writing proofs in the Acorn language. Triggers on: (1) Creating or editing .ac files, (2) Running acorn verify commands, (3) Formalizing math or crypto proofs, (4) Questions about Acorn syntax or standard library.
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Analyze any GitHub repository in AI-friendly format. Convert entire repos to single markdown documents, generate architecture diagrams with Mermaid, inspect structure trees, language breakdowns, and recent activity. Includes GitHub URL tricks, API shortcuts, and advanced search techniques. Read-only analysis — never executes code from repositories. Built for AI agents — Python stdlib only, no dependencies. Use for repository analysis, code architecture review, open source research, GitHub intelligence, repo documentation, and codebase understanding.
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。
AI-powered presentation generation using 2slides API. Create slides from text content, match reference image styles, or summarize documents into presentations. Use when users request to "create a presentation", "make slides", "generate a deck", "create slides from this content/document/image", or any presentation creation task. Supports theme selection, multiple languages, and both synchronous and asynchronous generation modes.
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。
Automate recruiting and hiring workflows in Ashby -- manage candidates, jobs, applications, interviews, and notes through natural language commands.
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。
Automate Apollo.io lead generation -- search organizations, discover contacts, enrich prospect data, manage contact stages, and build targeted outreach lists -- using natural language through the Composio MCP 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。
Automate Attio CRM operations -- search records, query contacts and companies with advanced filters, manage notes, list attributes, and navigate your relationship data -- using natural language through the Composio MCP 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。
Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".
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。
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
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。
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer
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。
Smart dependency management for any language. Auto-detects project type, applies safe updates automatically, prompts for major versions, diagnoses and fixes dependency issues.
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。
Language models exhibit predictable degradation patterns as context length increases. Understanding these patterns is essential for diagnosing failures and designing resilient systems.
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。
Transform technical git commits into polished, user-friendly changelogs and release notes. Automatically categorizes changes, translates developer language into customer-friendly copy, and generates professional changelog entries.
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。