Results for “doe”

Extract an Allium specification from an existing codebase. Use when the user has existing code and wants to distil behaviour into a spec, reverse engineer a specification from implementation, generate a spec from code, turn implementation into a behavioural specification, or document what a codebase does in Allium terms.

Use when investigating a bug, runtime error, unexpected behavior, test failure, or crash. For systematic root cause analysis, error message interpretation, stack trace reading, reproduction steps, and targeted fixes. Activate when the user says "it's broken", "this doesn't work", "I'm getting an error", or "help me debug".

Strip a problem to its irreducible fundamental truths and rebuild the solution from the ground up — free from analogy, convention, and inherited assumptions. Load when the user feels constrained by how something has always been done, when existing solutions feel expensive or inefficient for no good reason, when the user asks to think from first principles, challenge the fundamentals, or rebuild this from scratch. Also triggers on "why does it have to work this way", "what are the actual constraints here", "ignore what everyone else does", or when deep-thinking diagnoses a convention-break frame. Based on Aristotle's first principles method, popularised by Musk and Feynman. Produces genuinely novel solutions by eliminating convention.

Initiates a 6‑month trial of DHEA replacement in women with primary adrenal insufficiency (PAI) who have persistent low libido, depressive symptoms, or low energy despite otherwise optimized glucocorticoid and mineralocorticoid therapy. If the patient does not report a sustained beneficial effect after 6 months, discontinue DHEA.

Use to measure customer effort from behavioural signals instead of CES surveys, and to audit whether a composite effort score is honest. Trigger for "customer effort score", "behavioural CES", effort without survey, repeat contacts and channel switches, transfers and reopens, or "our CES doesn't match operational data".

Read and search GitHub repository documentation via gitmcp.io MCP service. **WHEN TO USE:** - User provides a GitHub URL - User mentions a specific repo in owner/repo format - User asks "what does this repo do?", "read the docs for X repo", or similar - User wants to search code or docs within a repo

Internal skill. Called by setup-evaluation after a PASS. Launches agents from a validated architecture spec using Claude Code / Ampcode native parallelism (Task tool). Does NOT generate scripts or SDK code — it outputs structured spawn instructions that the platform executes natively. Never invoked directly by the user. Never launches without a setup-evaluation PASS.

Authoritative guidance for building Claude Code skills, agents, and plugins, plus init and update steps that install and refresh the plugin-building skills in the current repository. Use when you need the rules or best practices for a skill, agent, hook, or plugin — designing, reviewing, hardening, or checking one against the guidance. Run with `init` to vendor the guidance, skill-builder, and agent-builder skills into the current repository (so they run with no dependency on this plugin) plus a path-scoped rule index, or `update` to refresh an already-vendored copy. Does not run an interview to build a new skill or agent from scratch — use skill-builder or agent-builder. Does not write feature code, review application code, or build non-plugin features.

Discover what bundled skills exist in this mimir install and what each one does. Use when you're not sure if a capability is already covered by a skill ("can I X?", "is there a skill for Y?", "what skills do I have?"). Reads SKILL.md frontmatter from each skill directory and surfaces names + descriptions.

Invoke only when the user explicitly asks to review code through the "single level of abstraction / layered error handling" lens — a function does only its own layer's business logic while errors are handled above or below. The agent reports detections, raw-count measurements, and move directions. Apply only when the user explicitly requests this lens.

Use to analyse the help-centre funnel from search through article view to contact, find actionable drop-off, and align KB content to contact drivers. Trigger for "self-service funnel", "contact after viewing an article", "why doesn't the help centre deflect", KB deflection rate, search-to-contact conversion, or article effectiveness.

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.

Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when "keywords, file_patterns, code_patterns, " mentioned.

Use to design or fix a customer support survey — CSAT, NPS, or CES — and to diagnose response bias. Trigger for "design a CSAT survey", "our CSAT doesn't match reality", "should we use NPS", survey response rate, non-response bias, survey timing or scale choice, comparing satisfaction across teams or channels, or interpreting a satisfaction trend.

Validate process decomposition and architecture design quality before execution begins. Load when the setup-evaluator agent fires (automatic for agent-chain tasks), or when user says "evaluate this setup", "check the decomposition", "validate the architecture", "is this plan sound", "review the agent design". Catches structural errors, missing knowledge, unrealistic step ordering, and topology mismatches. Does NOT modify — only evaluates.

Generate a PR description from the current branch's changes against a GitHub PR, using the gh CLI. Use when writing, drafting, or updating pull request descriptions, PR summaries, or PR bodies. Does not review code or post review comments — use code-review for local review or post-code-review-to-pr for posting a review to GitHub.

Use to test whether a support control actually operates, the way an auditor would test it, rather than confirming it exists on paper. Trigger for "test our controls", "does this control actually work", second-line assurance over support, control effectiveness testing, preparing for an internal audit, or a control that passed review and then failed in practice.

Query the bundled research knowledge graph for methodology guidance. Routes questions through a 3-tier knowledge base — WHY (research claims), HOW (guidance docs), WHAT IT LOOKS LIKE (domain examples) — plus structured reference documents. Returns research-backed answers grounded in specific claims with practical application to the user's system. Triggers on "/ask", "/ask [question]", "why does my system...", "how should I...".

Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.

Record observable skill test runs for debugging. Use when the user wants to test, dry-run, debug, inspect, or compare how a Codex skill behaves on a concrete request; creates a local non-overwriting Markdown report with the visible process, files read, commands run, changed artifacts, errors, and a brief behavior summary. Does not certify skill quality or replace user judgment.

Use as the entry point for any PMLA (Publications of the Modern Language Association) manuscript. Routes to the right PMLA sub-skill based on where you are in the lifecycle and which venue fits — a regular blind-reviewed article or a special feature (Theories and Methodologies, The Changing Profession, Criticism in Translation, Little-known Documents). It dispatches; it does not draft content.

Proposal research workflow that matches local case studies and gathers web evidence into an HTML research dossier. Use when the user needs proposal research, client intel, tech stack discovery, pricing benchmarks, competitive context, or case-study matching for a brief. Triggers: 'research this proposal', 'build a research dossier', 'match case studies', 'find pricing benchmarks', 'client intel for', 'what tech does X use'.

Diagnose and audit SEO issues affecting crawlability, indexation, rankings, and organic performance. Use when the user asks for an SEO audit, technical SEO review, ranking diagnosis, on-page SEO review, meta tag audit, or SEO health check. This skill identifies issues and prioritizes actions but does not execute changes. For large-scale page creation, use programmatic-seo. For structured data, use schema-markup.

This skill should be used when the user asks to "understand a codebase", "get code context", "research a library", "explore a repository", "find code examples", "look up documentation", asks a natural-language code/technology question (e.g. "how does X work", "X vs Y", "best practice for Z"), or wants to understand how a specific project, library, or concept works before making changes.

Cypress E2E testing framework. Covers commands, assertions, and component testing. Use for end-to-end testing. USE WHEN: user mentions "cypress", "e2e test", "cy.get", "cy.visit", asks about "cypress intercept", "component testing", "cypress commands" DO NOT USE FOR: Unit tests - use `vitest` or `jest`; Multi-tab scenarios - Cypress doesn't support; Native mobile apps - use Appium; Performance testing - use dedicated tools

Use to map where support conversation data actually goes — systems, vendors, countries, AI providers — and compare it against what the privacy notice and records say. Trigger for "where does our support data go", "map our data flows", "which vendors process our conversations", cross-border transfer review, ROPA accuracy for support, or a new tool that was connected without a review.

Install, configure, operate, secure, automate, tune, troubleshoot, and recover restic backups across local, SFTP, S3-compatible, cloud, and REST backends. Use when creating or managing a restic repository, designing backup or retention policy, validating restores, handling repository health or locks, moving repositories, or building safe scheduled backup jobs. Do not use for a generic file-copy task that does not need encrypted, deduplicated snapshots.

Give your agent a budget, a target, and a deadline — it does the rest. Orchestrates DSL + Opportunity Scanner + Emerging Movers into a full autonomous trading loop on Hyperliquid. Race condition prevention, conviction collapse cuts, cross-margin buffer math, speed filter. 3 risk profiles: conservative, moderate, aggressive. Use when setting up autonomous trading, creating a trading strategy, or running a scan-evaluate-trade-protect loop.

Greenfield development path for products, tools, and systems that do not yet exist. G Stack validates the idea before anything is planned or built. Use when starting from zero: no existing codebase, no existing schema, no existing API that this extends. AUTO-FIRE immediately when the user says any of: - "new development", "/new-development [description]" - "I have an idea for [X]", "I want to build [X] from scratch" - "new product", "new tool", "new platform", "new application" - "build [X] — it doesn't exist yet", "start a new project" Do NOT use when an existing codebase already exists for the work — use /full-development for large brownfield work. If unsure: ask "Does any part of this already exist in code?" If yes → /full-development. This is the most token-intensive command. Use it when the investment is justified by the scope of what is being built.

Author pull requests with intent-separated commits, blast-radius disclosure, and verification evidence. Load when opening a PR, writing a PR description, separating refactor from feature commits, or summarizing a change set for review. Also triggers on "write the PR", "PR body", "intent-separated commits", "split refactor from feature", "pr summary", or after safe-change cycles complete. Extends git-workflow-and-versioning — does not replace it.

Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use `improve-animations` or `review-animations` instead. Source: github.com/emilkowalski/skills.

Review a code file or directory and produce an evidence-backed GitHub or Jira issue proposing bug fixes, performance improvements, modularity improvements, DRY refactors, file splitting, reusable helpers, and architecture-alignment work. Use when a user asks for a code review, technical-debt proposal, refactor proposal, quality audit, bug-risk review, architecture-alignment review, or issue creation. This skill proposes work; it does not modify code.

Inventory of the intelli-verse-x product portfolio — what each product is, its repo, primary tech, deployment status, and which other product/service it's coupled to. Use whenever the user mentions a product by name (Quizverse, IntelliverseX, Hyperframes, Brackt, IntelliverseSpace, Intelliverse-X-AI, Intelli-verse-X-SDK, content-factory, etc.) and you need the canonical pointer for what it does + where it lives.

Use to assemble a fair, evidence-backed coaching pack for a support agent's one-to-one from QA evaluations and conversation history. Trigger for "prepare a coaching session for X", "what areas does X need to improve", "areas of markdown for this agent", "what coaching opportunities stand out", "build a coaching agenda from these tickets", or preparing a weekly or monthly agent review.