skill-personalizer
Skill Personalizer audits and modifies installed or newly created Agent Skills to reduce friction and improve triggering accuracy for a specific user's environment, tools, directories, and workflows. Use it when a skill undertriggers, overtriggers, contains unnecessary prompts, or conflicts with local setup; do not use it when preparing a skill for public distribution.
git clone --depth 1 https://github.com/hqhq1025/skill-optimizer /tmp/skill-personalizer && cp -r /tmp/skill-personalizer/skills/skill-personalizer ~/.claude/skills/skill-personalizerSKILL.md
# Skill Personalizer ## Overview Audit and tune a skill for one user's real environment. The goal is not public portability; it is better triggering, less friction, and stronger fit with the user's actual tools, paths, style, and recurring tasks. ## When To Use - A user installs a skill from GitHub or creates one from scratch and wants it to fit their setup. - A skill undertriggers, overtriggers, asks unnecessary questions, or misses the user's preferred workflow. - A user asks whether an existing skill is good, broken, noisy, too long, conflicting, or worth keeping. - Local paths, aliases, memories, CLIs, MCP tools, or repo conventions should be reflected in the skill. Do not use when preparing a skill for public release; use `skill-generalizer` for that. ## Workflow 1. Inspect the target skill, installed copies, local memories, and real session evidence when available. 2. Run the audit checks in [audit-rubric.md](references/audit-rubric.md) when quality, trigger fit, or retention is unclear. 3. Identify the user's recurring phrasing, expected autonomy level, tools, directories, and verification habits. 4. Compare the skill's trigger conditions against real user requests that should or should not load it. 5. Edit only the target skill and bundled resources needed for personalization. 6. Add concrete local defaults, preferred commands, safety boundaries, and verification steps. 7. Preserve useful upstream behavior; document any intentional local divergence. 8. Validate with realistic prompts and a frontmatter/layout check. ## Personalization Rules - Personal details are allowed only if they improve this user's future execution. - Do not add brittle fallbacks that hide broken local setup. - Prefer real local evidence over generic best practices. - Keep trigger descriptions broad enough to catch the user's natural phrasing. - If editing an installed third-party skill, avoid changing upstream attribution or license text. ## References Read [audit-rubric.md](references/audit-rubric.md) for the diagnostic pass inherited from the original optimizer. Read [personalization-rubric.md](references/personalization-rubric.md) for local defaults, session evidence, and validation scenarios.
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.
Use when mining coding-agent session history, archived transcripts, memories, or repeated local work to discover recurring workflows that should become new Agent Skills.