Skill Generalizer
Use when turning local, private, or personal Agent Skills into publishable skills for GitHub, marketplaces, teams, or public sharing, especially when private paths, personal habits, credentials, internal hosts, or user-specific context must be removed.
MCP get_skill({ skillId: "skill-generalizer-a0787027" })Use this skill with your agent
Create a free account and connect via MCP
# Skill Generalizer ## Overview Convert a working local skill into a clean public artifact. The goal is to preserve the reusable technique while removing private context, personal assumptions, and machine-specific setup. ## When To Use - A user wants to publish, share, promote, open-source, or package a local skill. - A skill was born from personal workflows, private repos, local paths, transcripts, remote hosts, or team conventions. - The output needs to be useful to strangers without leaking the author's environment. Do not use for tuning a skill only for the user's own machine; use `skill-personalizer` for that. ## Workflow 1. Inspect the actual source skill and nearby repo files before judging. 2. If the source skill quality is unclear, run the audit checks from `skill-personalizer` first. 3. Separate the reusable capability from personal implementation details. 4. Redact or replace private names, paths, hosts, credentials, account IDs, transcripts, and one-off project facts. 5. Rewrite the skill around general triggering conditions, portable workflows, and bounded assumptions. 6. Keep `SKILL.md` concise; move long rubrics, examples, or scripts into bundled resources. 7. Check target-agent compatibility before writing install instructions or support claims. 8. Produce publication-ready packaging and honest promotion copy only when requested. 9. Verify frontmatter, file layout, install path, and at least one realistic usage prompt. ## Public Release Rules - Frontmatter `description` should describe when to use the skill, not summarize its workflow. - Public examples must be generic or explicitly sanitized. - Claims in README or marketplace copy must match files that actually exist. - Prefer portable commands and path placeholders over the author's home directory or private aliases. - If a personal detail is essential, turn it into a configurable variable with setup guidance. ## References Read [publication-rubric.md](references/publication-rubric.md) when doing a full release pass, redaction review, README rewrite, or promotional packaging. Read [platform-compatibility.md](references/platform-compatibility.md) before claiming support for Codex, Claude Code, Cursor, OpenCode, Gemini CLI, or other coding agents.
Related Skills
More skills in Software Engineering
Accessibility Standards
Comprehensive web accessibility standards based on WCAG 2.2 AA, with 38+ anti-patterns, legal enforcement context (EAA, ADA Title II), WAI-ARIA patterns, and framework-specific fixes for modern web frameworks and libraries.
Accord
Authoring unified specification packages across Business/Development/Design teams via staged elaboration (L0 Vision → L1 Requirements → L2 Team Detail → L3 Acceptance Criteria). No code. Use when authoring cross-team specs, building L0-L3 packages, or aligning Biz/Dev/Design on a single source of truth.
Acquire Codebase Knowledge
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
Acreadiness Assess
Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.
Acreadiness Generate Instructions
Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.
Acreadiness Policy
Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.
Explore Other Categories
Skills from other categories with shared topics
Skill Builder
Automatically detect source types and build AI skills using Skill Seekers. Use when the user wants to create skills from documentation, repos, PDFs, videos, or other knowledge sources.
Skill Personalizer
Use when auditing or adapting newly created, downloaded, forked, installed, or community Agent Skills to the user's tools, habits, directories, session history, and preferred workflows, especially when triggers feel wrong, noisy, or too generic.
Agent Skills File Guidelines
Guidelines for creating high-quality Agent Skills for GitHub Copilot