بنقرة واحدة
ask-questions-if-underspecified
Clarify requirements before implementing. Use when serious doubts arise.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Clarify requirements before implementing. Use when serious doubts arise.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Systematically verifies suspected security bugs to eliminate false positives, producing a TRUE POSITIVE or FALSE POSITIVE verdict with documented evidence for each. Use when asked whether a specific finding is real, exploitable, or a false positive, or to verify or validate a suspected vulnerability — not for hunting or discovering new bugs.
Runs external LLM code reviews (OpenAI Codex or Google Gemini CLI) on uncommitted changes, branch diffs, or specific commits. Use when the user asks for a second opinion, external review, codex review, gemini review, or mentions /second-opinion.
Creates custom Semgrep rules for detecting security vulnerabilities, bug patterns, and code patterns. Use when writing Semgrep rules or building custom static analysis detections.
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.
Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.
Scans Algorand smart contracts for 11 common vulnerabilities including rekeying attacks, unchecked transaction fees, missing field validations, and access control issues. Use when auditing Algorand projects (TEAL/PyTeal).
| name | ask-questions-if-underspecified |
| description | Clarify requirements before implementing. Use when serious doubts arise. |
Use this skill when a request has multiple plausible interpretations or key details (objective, scope, constraints, environment, or safety) are unclear.
Do not use this skill when the request is already clear, or when a quick, low-risk discovery read can answer the missing details.
Ask the minimum set of clarifying questions needed to avoid wrong work; do not start implementing until the must-have questions are answered (or the user explicitly approves proceeding with stated assumptions).
Treat a request as underspecified if after exploring how to perform the work, some or all of the following are not clear:
If multiple plausible interpretations exist, assume it is underspecified.
Ask 1-5 questions in the first pass. Prefer questions that eliminate whole branches of work.
Make questions easy to answer:
defaults to accept all recommended/default choices)1b 2a 3c); restate the chosen options in plain language to confirmUntil must-have answers arrive:
If the user explicitly asks you to proceed without answers:
Once you have answers, restate the requirements in 1-3 sentences (including key constraints and what success looks like), then start work.
1) Scope?
a) Minimal change (default)
b) Refactor while touching the area
c) Not sure - use default
2) Compatibility target?
a) Current project defaults (default)
b) Also support older versions: <specify>
c) Not sure - use default
Reply with: defaults (or 1a 2a)