Enforces pixel-perfect implementation of Figma designs by exhaustively extracting every visual property from Figma, spinning up Chrome DevTools to measure the current implementation, building a full comparison checklist, and fixing all discrepancies in a single pass. MUST be triggered whenever implementing UI from Figma, fixing styling to match Figma, or any time the user says "match Figma", "check against Figma", "compare to design", "the design doesn't match", "colors are wrong", "spacing is off", or references a Figma URL in a styling context. Also trigger when you just finished writing CSS/styling code that was informed by a Figma design. This skill is NON-OPTIONAL when Figma designs are involved in styling work.
Create well-structured tickets as reviewable markdown files, then push to any tracker (Jira, Linear, Trello, Asana, Shortcut) via MCP or CLI after user review. Grounds each ticket in actual code by calling /flagrare:codebase-explore before drafting, and polishes the Context section via /flagrare:write-docs. Use when the user asks to create tickets, file bugs, write stories, create tasks, build a backlog, or convert specs/TDDs into implementation tickets.
Review pull requests with full context. Fetches linked Jira tickets, Figma designs, and Notion docs via MCP, spawns parallel subagents for systematic code review (correctness, security, tests, SOLID, clean code), then drafts friendly, humanized GitHub-ready comments. Use when reviewing PRs, examining code changes, or when the user asks for a code review.
Scan the org's communication surfaces (chat like Slack or Teams, open PRs, RFC docs and design docs, ticket threads, whichever MCPs are connected) for high-leverage discussions the user should weigh in on, decisions still being formed, people stuck or circling, questions squarely inside the user's domains, cross-team changes touching systems they own or depend on. Built for engineers working toward promotion, it hunts opportunities to operate at the next level (influence beyond assigned work), ranks them by leverage and credibility, drafts replies in the user's own voice for approval, and logs posted contributions as promotion evidence that /flagrare:brag-doc can later consume. Use whenever the user says "senior scan", "promo scan", "what needs my attention", "where should I weigh in", "anything I should jump into", "scan slack", "scan PRs", "catch me up on what's happening", or any variant of "where can I have the most impact today", even when the skill isn't named. Also trigger when the user talks about wan
Pre-commit quality gate. Invoke before every git commit, after /flagrare:staleness-audit. Seven checks, plan gaps, use-case coverage gaps, missing test scenarios, test philosophy violations (Kent Dodds Testing Trophy), SOLID violations, Clean Code violations, and security vulnerabilities. Each check is delegated to a parallel subagent. Surfaces findings before they land in history. Also invoke when the user says review this, am I done, did I miss anything, or check the quality.
Focused security review of a change. Finds HIGH-CONFIDENCE, concretely exploitable vulnerabilities in the staged diff (injection, broken authn/authz, secrets and data exposure, unsafe deserialization, crypto misuse, SSRF) and audits dependencies when a lockfile moved, using the repo's own package manager. Runs as Check 7 of /flagrare:implementation-review, and standalone when the user says 'security review', 'security audit', 'check this for vulnerabilities', 'is this safe', 'any security holes', 'threat check', or before shipping anything that touches auth, user input, secrets, or untrusted data. Reports only findings with a concrete exploit path, never theoretical noise.
Post-implementation quality gate. Runs automated checks (tests, lint, types), invokes /flagrare:implementation-review for the seven-check parallel review, then performs additional SOLID and Clean Code review on any findings not covered. Use when the user says 'wrap up', 'review changes', 'check my work', 'am I done', or after completing an implementation task.
Review a finished or near-finished document the way a human editor reads it, start to finish, building a model of what it's trying to communicate, then diagnosing cohesion, coherence, narrative throughline, pacing, consistency, reading fluency, contextualization, and clarity across the whole piece, never just line-by-line. Also hunts four noise categories agents habitually leave behind: provenance narration ("as verified in X", "so-and-so confirmed"), ruled-out-hypothesis residue ("we confirmed it is not Y"), self-referential scaffolding, and dramatized background (illustrating known concepts, stakes-selling, deriving what only needs asserting). Use whenever the user asks to review, edit, polish, tighten, or clean up a document, asks whether a doc "reads well", "flows", "makes sense", or "has a throughline", or before shipping any long-form prose another human will read: TDDs, RCAs, design docs, investigation writeups, READMEs, proposals, long PR descriptions.