AI & ML

jamie-bitflight Skill

Use when orchestration or planning agents are producing task plans, task prompts, or TASK.md instructions that must be unambiguous, verifiable, and resistant to hallucination. Applies CLEAR (Concise, Logical, Explicit, Adaptive, Reflective) to structure and write agent task prompts, then adds CoVe (Chain of Verification) checks where accuracy risk is meaningful. Activates on draft task prompts, swarm plans, migration tasks, and multi-step plans requiring independently executable steps.

jamie-bitflight Bundle

Manages feature implementation task state via SAM MCP tools. Use when querying task status, listing ready tasks, claiming tasks for execution, updating task timestamps, or coordinating multi-task feature rollout. Activated by the /dh:execution orchestrator to track progress — also activates directly when managing tasks or configuring hook profiles.

jamie-bitflight Skill

Linter-specific resolution workflows for ruff, mypy, pyright, and basedpyright. Provides systematic root-cause analysis procedures, suppression gates, and verification steps. Use when resolving linting errors as a sub-agent, implementing fixes systematically, or conducting type flow analysis.

jamie-bitflight Bundle

Use when debugging software, investigating incidents, diagnosing flaky tests, or analyzing performance regressions — enforces structured observation recording with evidence IDs, causality validation, and verification gates to prevent correlation-causation pollution. Use when an agent might otherwise summarize or speculate instead of reporting observed evidence.

jamie-bitflight Skill

Routes Python engineering tasks to specialist skills by matching trigger patterns before any architecture, plan, or code is written. Use when working with Typer CLI frameworks, Rich or Textual terminal UIs, CLI UI/UX design, questionary prompts, FastMCP/MCP servers, ty type checker, uv package manager, Hatchling build backend, TOML editing, pre-commit/prek hooks, async Python, PyPI packaging, complex linting, technical debt modernization, testing workflows, feature development, or stdlib-only scripting.

jamie-bitflight Skill

Use when a task asks for architecture review, dependency graph visualization, module coupling analysis, or circular dependency detection. Auto-detects scope (git diff → PR diff → full project). Reads project config (pyproject.toml, tsconfig.json, go.mod, Cargo.toml) to establish the intra-project module namespace before parsing imports. Builds a module-dependency graph across Python, TypeScript, JavaScript, Go, Rust, and Java. Detects cycles via graphify output or an executable Python script. Checks Conway's Law alignment against CODEOWNERS and directory structure. For Claude plugin repos, also traces cross-language chains: hook configs → hook scripts, SKILL.md/agent docs → node/uv-run scripts, PEP 723 inline deps, and MCP tool calls. Emits Mermaid flowcharts with severity color-coding (red = circular dep, yellow = high-coupling, green = clean, blue = Conway violation). Applies recursive semantic partitioning for graphs > 40 nodes. Registers each diagram as a codebase-analysis artifact.

jamie-bitflight Bundle

Complete reference for Claude Code plugins system (April 2026). Use when creating plugins, understanding plugin.json schema, marketplace configuration, bundling skills/commands/agents/hooks/MCP/LSP/monitor servers, plugin caching, validation, or distribution. Covers plugin components, directory structure, installation scopes, environment variables, CLI commands, debugging, and enterprise features.

jamie-bitflight Skill

Loaded automatically when reviewing Claude skills or agent definitions — covers SKILL.md structure, frontmatter validity, token budget, description quality, and agent contract compliance.

harshahosur81 Skill

Master C#/.NET backend development patterns for building robust APIs, MCP servers, and enterprise applications. Covers async/await, dependency injection, Entity Framework Core, Dapper, configuration, caching, and testing with xUnit. Use when developing .NET backends, reviewing C# code, or designing API architectures.

harshahosur81 Skill

Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.

harshahosur81 Skill

This skill should be used when the user asks to "create financial projections", "build a financial model", "forecast revenue", "calculate burn rate", "estimate runway", "model cash flow", or requests 3-5 year financial planning for a startup.

jamie-bitflight Bundle

Orchestrator context window discipline enforcement. Prevents the orchestrator from reading source files it will not edit, running diagnostic commands that waste context, and rationalizing delegation bypasses. Use when setting up orchestrator guardrails, reviewing delegation discipline, or diagnosing context window waste in multi-agent workflows. Activates PreToolUse hooks that surface decision points before source file reads and diagnostic command execution.

jamie-bitflight Skill

Analysis criteria, transformation patterns, output format, and validation checklist for refactoring Claude Code agent prompt files. Load this skill when preparing to run the subagent-refactorer agent or when reviewing agent prompt files for structural, model optimization, or instruction quality improvements.

jamie-bitflight Bundle

Claude Code session log schema — JSONL record types, message structure, tool call/result pairing, subagent file locations, team session layout, task/plan/team configuration paths. Use when parsing ~/.claude/projects/**/*.jsonl files, writing PostToolUse hooks that measure response sizes, building session analyzers, or any agent that reads or queries Claude session transcripts.

jamie-bitflight Skill

Provides agent selection criteria, workflow patterns (TDD, feature addition, code review, refactoring, debugging), quality gates, and python-cli-architect vs stdlib-scripting routing for Python engineering tasks. Activated by python-engineering:orchestrate at Step 1 before any task is routed. Also activates when an orchestrator needs to select the correct Python specialist agent or chain agents across a multi-step Python workflow.

jamie-bitflight Skill

Shared Python 3.11+ development standards covering type safety (ty, native generics, Protocol, TypeIs), layered architecture, error handling, performance, identifier naming, UI/CLI patterns (Rich/Typer), testing requirements (pytest, 80% coverage, TDD), and quality gates. Activates when any Python skill or agent needs to apply shared standards for implementation, code review, refactoring, or test authoring.

jamie-bitflight Skill

Single-pass SOLID review — dispatches one reviewer over the complete ruleset, emitting the fixed candidate schema.

stevenke1981 Skill

當使用者需要「AI 中世紀視覺提示專家」處理AI 生成相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把目標、受眾與風格限制轉成可直接使用的創作交付物，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「小說家」處理藝術文創相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把目標、受眾與風格限制轉成可直接使用的創作交付物，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「藥師」處理醫療健康相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再整理症狀、風險訊號、照護選項與就醫準備資訊，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「IT 支援工程師」處理科技資訊相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把需求轉成可實作、可測試、可回滾的工程方案，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「文案寫手」處理媒體傳播相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把目標、受眾與風格限制轉成可直接使用的創作交付物，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「生涯教練」處理服務飲食相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把顧客需求、服務標準、資源限制與例外狀況轉成可執行的服務方案，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「占星解讀師」處理宗教靈性相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再以反思、象徵與文化脈絡協助使用者整理問題與行動選項，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「民事法官」處理法律司法相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再整理法律問題、事實時間線、文件重點與需諮詢律師的議題，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「UX 設計師」處理科技資訊相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把需求轉成可實作、可測試、可回滾的工程方案，並輸出證據、風險、下一步與需要人工覆核的事項。

peparhugo Bundle

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

delorenj Bundle

Run a real-time AI phone agent using Twilio, Deepgram, and ElevenLabs. Handles incoming calls, transcribes audio, generates responses via LLM, and speaks back via streaming TTS. Use when user wants to: (1) Test voice AI capabilities, (2) Handle phone calls programmatically, (3) Build a conversational voice bot.

delorenj Bundle

Single-source-of-truth config fan-out: keep ONE master file (e.g. hooks.master.json) and propagate it to many downstream targets that each have their own native format/dialect, with a lock file (hooks.mappings.lock.json) recording how ambiguous/divergent mappings were resolved so re-syncs are seamless. Reference implementation: bloodbank services/agent-hooks — hooks.master.json → sync.py → per-agent generated configs + event_map.generated.json, gated by `mise run hooks:check` / `hooks:sync`. Use when adding a new agent CLI or target to agent-hooks, editing hooks.master.json, fixing generated-config drift, resolving an ambiguous mapping, or designing a NEW master-config → multi-dialect propagation engine with ambiguity-resolution memory. Keywords: SSOT, single source of truth, fan-out, generated-config drift. Do NOT use for bumping versions across files (use mise-versioning), defining event schemas or the event-naming contract, or single-target config templating with no dialect/ambiguity dimension.

delorenj Bundle

Deepgram API reference for speech-to-text, text-to-speech, voice agents, audio intelligence, and account management. Use whenever building with Deepgram APIs — REST or WebSocket. Covers authentication, all endpoints, query parameters, request/response schemas, and WebSocket message formats. Reference files are organized by domain: listen (STT — Nova and Flux STT), speak (TTS — Aura and Flux TTS), agent (voice agents), read (text/audio intelligence), models, projects, auth, and self-hosted.

delorenj Skill

Start a voice conversation using the Pipecat MCP server

stevenke1981 Skill

當使用者需要「外匯市場分析師」處理金融商業相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再建立可稽核的財務分析、情境假設、風險揭露與決策摘要，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「播客主持人」處理媒體傳播相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把目標、受眾與風格限制轉成可直接使用的創作交付物，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「銷售教練」處理銷售相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再建立以客戶需求、資格判定、價值證據與下一步為核心的銷售流程，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「公關專員」處理媒體傳播相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再把目標、受眾與風格限制轉成可直接使用的創作交付物，並輸出證據、風險、下一步與需要人工覆核的事項。

stevenke1981 Skill

當使用者需要「公務行政專員」處理政府公務相關任務時啟動。本 Agent 會先確認目標、資料來源、限制與驗收標準，再用證據、利害關係人與政策影響框架整理公共議題，並輸出證據、風險、下一步與需要人工覆核的事項。