Agent Workflow Claude Skills

Configure an MCP server for GitHub Copilot with your Dataverse environment.

>- Transforms vague prompts into optimized Claude Code prompts. Adds verification, specific context, constraints, and proper phasing. Invoke with /best-practices.

Create agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation.

Multi-agent autonomous startup system for Claude Code. Triggers on \"Loki Mode\". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations,...

Authenticate to websites with human-in-the-loop browser handoff. Use when user needs to log into a website, complete 2FA, or solve CAPTCHAs for agent access.

Use when reviewing SKILL.md files for structure and trigger quality.

| Print a human-readable index of every skill in this repository, grouped by family prefix (`pr-management`, `security`, `setup`, …) with each skill's name and the first sentence of its `description`. The listing is generated on every run from the live `.claude/skills/*/SKILL.md` files, so it never goes stale when skills are added, removed, or rewritten.

| Fan a local diff through three independent, axis-focused review passes (correctness, security, conventions), then merge the findings into a single structured report. Each pass is isolated so findings from one axis cannot suppress or bias the others. The merged report uses the same format as pairing-self-review so the developer gets a consistent signal regardless of which Agentic Pairing skill they invoke.

| Optimize an existing framework skill (or sweep a set of them) by applying the restructuring patterns proven on the security-skill lift concrete/project-specific values out of the body into `<project-config>` placeholders, replace in-agent-context body reads with out-of-context tool calls, batch per-item fetches into a single upfront pass, and add a deterministic pre-flight no-op classifier ahead of LLM passes. Every change is a behavior- preserving proposal the maintainer signs off on; the skill validator must stay green before and after. The refactoring sibling of `write-skill` (which authors net-new skills).

| Probe the secure-agent setup for in-session functional restrictions that block legitimate workflows. Three live probes — SSH agent / Yubikey reachability, localhost port binding, docker / podman runtime socket — each pointing the user at the matching numbered troubleshooting entry and its settings.json remediation (see body). Read-only — never modifies settings.json, never invokes the sandbox bypass.

| Guide an adopter through the first-time install of the framework's secure agent setup (bubblewrap + socat + claude-code, sandbox/permissions/clean-env layers). Walks every step interactively; never auto-runs sudo, shell-rc edits, or settings overwrites.

| Walk an adopter through promoting a local `.apache-magpie-overrides/<skill>.md` file into a PR against `apache/magpie`. After the PR merges and the adopter runs `/magpie-setup upgrade`, the override file is no longer needed and the skill prompts for its removal.

| Show how the apache-magpie framework is adopted in the current repo, then adjust that setup in place. Renders a Markdown agent targets, the installed skill families, and symlink health. From the same view the user can add or drop agent targets and skill families; the actual change runs through the setup skill.

| Turn a framework bug or quirk the agent hit while running a Magpie skill or tool into a fix PR against `apache/magpie` — one PR per issue. First confirms the problem is a framework defect (not a local misconfiguration or a stale snapshot), then searches `apache/magpie` for an existing issue or PR that already covers it, and only proposes a new fix PR when none exists — otherwise it points the user at the pending one.

| Compare two near-duplicate skills — typically an ASF variant and a non-ASF or multi-project variant — and classify every difference as ALLOWED, DRIFT, or SAFETY-BASELINE. Produces a structured diff and convergence is a separate confirmed authoring step. A safety-baseline divergence is always a must-fix, never silently merged into allowed-divergence noise.

| Author a new skill for the Apache Magpie framework, or update an existing one. Walks the user through the framework's skill shape (frontmatter, resources, placeholder convention, prompt-injection defences, Privacy-LLM gate-check) and validates via the framework's existing [`tools/skill-and-tool-validator`](../../tools/skill-and-tool-validator/). Scaffolds new skills via `init_skill.py`.

Integration patterns for Mapbox MCP Server in AI applications and agent frameworks. Covers runtime integration with pydantic-ai, mastra, LangChain, and custom agents. Use when building AI-powered applications that need geospatial capabilities.

> Generate an /insights-style HTML report across MANY of your agent coding sessions your friction points, and concrete fixes to become more effective — precise goal-setting, not trusting output blindly, scoping, context hygiene, right-sizing models. Reads local session history and writes one self-contained report.html. Use when the user asks to "разбери мои сессии", "оцени как я работаю с агентом", "мой insights", "session insights report", "review how I work", "на что обратить внимание", or runs "/mentor", "/mentor claude", "/mentor codex", "/mentor both". Do NOT use for reviewing the CODE produced (that's code-review) or building the agent.

Use when users ask to discover, install, list, check, update, remove, back up, restore, sync, or initialize Agent Skills, mention `bunx skills`, `npx skills`, `skills.sh`, or `skills-lock.json`, ask "find a skill for X", or want help extending agent capabilities with installable skills.

Use when routing Claude Code through a local LiteLLM proxy to GitHub Copilot, reducing direct Anthropic spend, configuring ANTHROPIC_BASE_URL or ANTHROPIC_MODEL overrides, or troubleshooting Copilot proxy setup failures such as model-not-found, no localhost traffic, or GitHub 401/403 auth errors.

Provides the vendored agent-style v0.3.5 prose rule pack as a portable Claude skill. Use when installing, syncing, applying, or auditing SDD Agent-Style support in another project, or when a style-review workflow needs the bundled rules.

Turns real agent failures, repeated prompts, team-specific workflows, and durable project lessons into better SDD skills or memory entries. Use when the user asks to create/update/refine skills, extract reusable lessons, improve skill routing, encode team process, or save patterns for future sessions.

Evaluates Agent Skills (Cursor / Claude / OpenClaw compatible) and produces a quantitative, rubric-based score with actionable improvement suggestions. Use when the user asks to review, rate, audit, grade, lint, or improve a SKILL.md file, a skill folder, or a skill archive, or says things like "给这个 skill 打分", "评估一下 skill 质量", "audit this skill", "rate my agent skill".

Route broad or ambiguous VitaeContext work to the right module while keeping context scoped. Use when a request spans multiple surfaces, asks for overall digital-presence strategy, involves provider or install architecture, needs agent-context planning, or the correct platform skill is unclear.

The philosophy and practical benefits of agent fungibility in multi-agent software development. Why homogeneous, interchangeable agents outperform specialized role-based systems at scale.

Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.

Guide for creating Claude Code skills following Anthropic's official best practices. Use when user wants to create a new skill, build a skill, write SKILL.md, update an existing skill, or needs skill creation guidelines. Provides structure, frontmatter fields, naming conventions, and new features like dynamic context injection and subagent execution.

Orchestrates knowledge pack content generation pipeline: batch scheduling, completion tracking, cross-pack dependency ordering, and validation triggering. Use when coordinating pack generation across phases 245-251.

Creates context handoff documents for session continuity. Use when ending sessions, switching tasks, or handing off work.

> Project state awareness and session recovery for GSD-managed projects. a break, the user asks "where did we leave off" or "what's the current state", before making substantial code changes (to check for existing plans), the user seems disoriented about project status, or when something seems off and STATE.md might have relevant context. Also activates when the user references .planning/ files, milestones, phases, or project progress.

> Use when parallel agents in a convoy or across git worktrees hit a write conflict on shared state — a git tree, a config, or a shared document — and you must decide whether the conflict is semantically real. Classifies each conflicting hunk as independent (keep both), redundant (pick one), or a genuine clash (escalate), instead of blind locks, abort-and-retry, or wraps an LLM judgment, defaults to escalate on any uncertainty, and unconditionally escalates any hunk touching .planning/, config, credentials, or safety-critical paths. Backed by CoAgent (arxiv 2606.15376v1). Triggers on write conflicts between parallel agents on shared repo state.

Conversational guide for using tools/session-retro/observe.mjs to capture friction, wins, corrections, decisions, gaps, tool-use, and checkpoints as they happen during a session. Use at session start (to kick off the log), at inflection points (to record events), and at session end (to archive and feed the retrospective generator).

> Use when reviewing, shipping, or regression-testing a SKILL.md and you hold one or more captured trajectories where that skill was actually loaded. Translates the skill's instructions into behavior constraints, then reports which were EXERCISED (coverage) versus untested, and flags any that were in-scope but VIOLATED (compliance) — a cheap single-trajectory test-adequacy gate. It surfaces untested instructions rather than auto-blocking, and escalates fail-closed only when a violation touches shared repo state, never-surface memory, or self-modification. Complements skill-counterfactual-audit (which measures EFFECT) and skill-causal-curation (which measures contribution); this one asks ADEQUACY. Backed by the agent-skill-coverage metric (arxiv 2606.20659v2). Triggers on skill review, ship gating, and regression-testing a skill against its trajectories.

> Audit a skill by running a paired probe — the same task once with the skill loaded and once without — segment both traces into goal-directed phases, align phases, and emit a SIP report (surface anchoring, template copy, excess planning, task recovery, off-task artifact). Use whenever a skill is created, modified, or proposed for retirement. shows a single skill can produce 522 measurable behavioural changes this skill", "is this skill helping", "retire skill", "before shipping skill", "behavioural impact of skill X", or any skill review event.

Use when the user asks to forge, scaffold, author, or ship a new skill or agent — the skill-creator's own namesake artifacts. Drives the skill-forge loop (create → fill → validate → critique → ship → publish) via the skill-creator CLI.

Use when authoring or reviewing a SKILL.md or agent .md and you need to detect and fix the four most common frontmatter defects — echoed or truncated triggers, tools written as a YAML array instead of a comma-separated string, a description outside the 1-1024 character bound, and a missing "Use when..." clause.

> Manages skill-creator integration with GSD workflows including skill loading, session observation, bounded learning guardrails, and pattern relevant skills are loaded first), starting or resuming a work session (to check for pending suggestions), the user asks about skills, patterns, or skill-creator status, performing code changes that might represent repeating patterns, the user corrects Claude's output (highest-signal observation), or when skill refinement, creation, or suggestion review is discussed. Critical for maintaining the adaptive learning layer.

Transform a user's builder vision into a complete, executable GSD mission package. Use this skill whenever a user has described what they want to BUILD (a product, tool, feature, system, educational pack, or ecosystem component) and wants it structured for GSD execution. Triggers include: 'structure this for GSD', 'make this into a milestone', 'turn this vision into a mission', 'package this up for Claude Code', 'create the mission files', 'I want to hand this to GSD', 'make me a mission package', or any request to decompose a described system into wave-based executable tasks. Also trigger when the user has a vision doc already written and needs mission decomposition. Prefer this skill over generic document creation whenever the GSD ecosystem is mentioned alongside building something.

> Use when you have captured session evidence — session-retro / session- observatory-live traces in .planning/patterns/, tool logs, correction records — and want to induce a reusable skill from it. Segments the traces into candidate skill units (an LLM judgment, not a deterministic parse) and structure, execution semantics, and runtime attachments (verification, safety, rollback, state). It emits a spec object, NOT a finished SKILL.md, and hands that spec to skill-forge. It sits between skill-integration (upstream frequency detector) and skill-forge (downstream author). Backed by Agent-Trace-to-Skill Induction (arxiv 2606.06893v1). Triggers on inducing a skill from captured traces, turning a repeated pattern into a skill spec, and preparing evidence for skill-forge.

Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.

Use when creating or updating AGENTS.md files, .github/copilot-instructions.md, or other AI agent rule files, onboarding AI agents to a project, standardizing agent documentation, or when anyone mentions AGENTS.md, agent rules, project onboarding, or codebase documentation for AI agents.

Creates minimal, effective AGENTS.md files using progressive disclosure. Triggers on "create agents.md", "refactor agents.md", "review my agents.md", "claude.md", or questions about agent configuration files. Also triggers proactively when a project is missing AGENTS.md.

Reviews and validates agent skills against best practices. Triggers on "review this skill", "check my skill", "validate skill", "is this skill well-written", or when creating/editing skills.

Formula WorkPaper runtime and MCP server for AI agents and Node.js services. Use when an agent needs spreadsheet-style formulas, cell edits, recalculation, readback verification, or persisted WorkPaper JSON without driving Excel UI.

Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.