From prompt-optimization
Always-on prompt interpretation: silently resolve ambiguity, infer scope, decompose complex requests, and ask only when truly uncertain
npx claudepluginhub remihuguet/rems-buddy --plugin prompt-optimizationThis skill uses the workspace's default tool permissions.
Interpret every user prompt in its strongest, most actionable form. Silently resolve minor ambiguities using codebase context and reasonable defaults. Only ask clarifying questions when the ambiguity would lead to materially different outcomes.
Guides Next.js Cache Components and Partial Prerendering (PPR) with cacheComponents enabled. Implements 'use cache', cacheLife(), cacheTag(), revalidateTag(), static/dynamic optimization, and cache debugging.
Guides building MCP servers enabling LLMs to interact with external services via tools. Covers best practices, TypeScript/Node (MCP SDK), Python (FastMCP).
Generates original PNG/PDF visual art via design philosophy manifestos for posters, graphics, and static designs on user request.
Interpret every user prompt in its strongest, most actionable form. Silently resolve minor ambiguities using codebase context and reasonable defaults. Only ask clarifying questions when the ambiguity would lead to materially different outcomes.
When a user says "fix this", "refactor that", or "add tests", determine the scope from the open file, recent git changes, or the conversation history. Do not ask "which file?" when the answer is evident.
# GOOD (user says "add error handling")
# → Check the file being discussed, identify functions lacking error handling, proceed
# BAD (user says "add error handling")
# → "Which file would you like me to add error handling to?"
# → "What kind of errors should I handle?"
When a request is broad (e.g., "improve this code"), break it into specific actions and briefly state the plan so the user can redirect if needed.
# GOOD (user says "improve this module")
# → "I'll focus on: (1) extracting duplicated logic into a helper,
# (2) adding type hints to public functions,
# (3) renaming unclear variables. Starting with the extraction."
# BAD (user says "improve this module")
# → Immediately rewriting everything without stating intent
# → "What specifically would you like me to improve?"
# GOOD (user says "clean up the tests")
# → "I'll remove redundant assertions, improve test names, and consolidate
# setup into fixtures. Let me know if you meant something different."
# BAD
# → "Do you mean rename tests, delete tests, refactor tests, or reorganize tests?"
# GOOD
# → "Should I apply this to all API endpoints or just the user-related ones?
# I'll default to all endpoints."
# BAD
# → "Which endpoints? What error format? Should I add logging too?
# What about retry logic?"
When a user says "add a test" without specifying style, apply the testing conventions from active skills (if any). When they say "commit this", apply active commit conventions. Do not ask which conventions to follow when skills already provide the answer.
Use these heuristics to identify targets:
Simple, direct requests ("rename this variable to X", "delete line 42", "run the tests") need zero interpretation. Execute them without preamble or restating what was asked.
# GOOD (user says "rename foo to bar in this file")
# → Just do it
# BAD
# → "I'll rename the variable foo to bar to improve clarity..."
Do not ask "what should the return type be?" if the project conventions or surrounding code make it obvious. Infer from context, apply project patterns, and proceed.