Results for “verification”

Standard reviewer for correctness and reproducibility. Use when the user asks to talk to Omen, requests a code review, or needs reproducibility verification.

Classify whether a ticket is frontend or UI work. Use when deciding whether design-aware planning, visual verification, UI tests, or screenshot capture applies.

Popconfirm component for confirmation dialogs in popover style. Invoke when user needs to implement confirmation prompts, delete confirmations, or action verifications in Naive UI.

Provides a structured protocol for receiving and evaluating code review feedback, emphasizing technical verification over performative agreement.

Automate email validation and mailbox verification tasks using the Mailboxlayer API through Composio's Rube MCP integration.

Enforces code review practices: receiving feedback with technical rigor, requesting reviews via /code-review, and verifying before claiming completion.

Analyze a problem, plan the fix, execute with verification. Use when tackling a non-trivial bug, feature, or refactor that needs structured approach.

Get Shit Done - Full project planning and execution workflow. Handles project initialization with deep context gathering, automated research, roadmap creation, phase planning, and execution with verification.

Provides a structured debugging workflow for errors, test failures, and unexpected behavior, including root cause analysis and verification steps.

Deploy and verify smart contracts on Base with Foundry, including testnet faucet access, encrypted keystore management, and BaseScan verification.

Implement Ed25519 digital signatures for document signing, code signing, and API authentication using Python.

Edits a specific page in a PDF using a natural-language instruction, with page-number handling and output verification.

Provides structured debugging guidance for errors, test failures, and unexpected behavior, including root cause analysis and verification steps.

Test Python services with pytest, async coverage, monkeypatch, and boundary-focused fakes. Use when writing Python tests, fixtures, async tests, regression tests, or dependency-isolated verification.

Configure Python tooling, dependency surfaces, static analysis, and verification gates. Use when editing `pyproject.toml`, `requirements.txt`, `pytest.ini`, `ruff`, `pyright`, CI, or Python release checks.

Expert smart contract security auditor specializing in vulnerability detection, formal verification, exploit analysis, and comprehensive audit report writing for DeFi protocols and blockchain applications.

Automates visual testing and UI interaction verification using browser automation after deploying features.

Guides implementing features and bug fixes test-first, enforcing red-green-refactor with mandatory failure verification.

Runs a structured bug-fix pipeline that scouts, diagnoses, fixes, reviews, and finalizes code changes with optional quality re-verification.

Evaluates execution transcripts and output files against a list of expectations, assigning pass/fail verdicts with cited evidence and critiquing the assertions themselves.

Provides a structured debugging workflow for diagnosing errors, test failures, and unexpected behavior, including root cause analysis and verification steps.

Launches long-running evaluation batches in isolated tmux sessions with pre-flight verification, monitoring, and post-flight analysis for unattended runs.

Provides a structured debugging workflow for diagnosing errors, test failures, and unexpected behavior, including root cause analysis and fix verification.

Formally verify programs by writing Lean 4 proofs. Trigger this skill whenever the user wants to formally verify code, generate Lean 4 proofs, prove properties about algorithms or smart contracts, verify invariants, convert program logic into formal specifications, or anything involving Lean 4 and formal verification. Also trigger when the user mentions "qedgen", "lean proof", "formal proof", "verify my code", "prove correctness", "formal verification", or wants mathematical guarantees about their implementation.

Grounds every implementation decision in official documentation, ensuring authoritative, source-cited code free from outdated patterns.

Watch, audit, and fix another agent's work by reconstructing the original request, inspecting evidence, and reporting gaps.

Uses two independent review agents to verify output quality, requiring both to pass before shipping.

Creates a concrete, multi-phase plan before starting a multi-file refactor, including affected files, dependencies, verification steps, and rollback procedures.

Generates complete, copy-paste ready implementation documentation from a PR plan, including code blocks and verification checklists.

Generate native .pptx slides using PptxGenJS with strict design rules, color palette adherence, and automated QA verification.

Test JWT signature verification bypass by crafting tokens with the 'none' algorithm.

Coordinate large-scale codebase migrations and multi-file refactors across hundreds of files using batched PRs and CI verification.

Identifies and removes dead code safely, with test verification at each step and categorization of risk levels.

Discovers, audits, repairs, adapts, and designs bounded AI-agent loops with explicit triggers, actions, verification, stopping conditions, guardrails, and handoffs.

Coordinate a full Galyarder Framework release across engineering verification, npm, GitHub, smoke testing, and announcement follow-up.

Provides guidelines for writing conventional commit messages and pull request descriptions, including merge strategy and GitHub username verification.