Search: "campaign"

Sets up and runs AFL++ for multi-core fuzzing of C/C++ projects built with afl-clang-fast or afl-gcc-fast. Covers instrumentation modes, parallel main and secondary campaigns, persistent mode, corpus minimization, and crash triage. Use when scaling fuzzing across cores, fuzzing a mature C/C++ codebase, reading the afl-fuzz status screen, or moving on after libFuzzer has plateaued.

Configures mewt or muton campaigns, analyzes surviving mutants, and investigates bugs exposed by testing gaps. Use when setting up mutation testing, reviewing campaign results, identifying equivalent mutants, or finding bugs from surviving mutations.

Sets up and runs libFuzzer, the coverage-guided fuzzer built into LLVM, on C/C++ code that compiles with Clang. Covers harness structure, -fsanitize=fuzzer builds, corpus and dictionary management, sanitizer integration, and campaign triage. Use when writing or debugging an LLVMFuzzerTestOneInput harness, starting fuzzing on a C/C++ library, choosing between libFuzzer and AFL++, or working out why a libFuzzer run finds nothing.

Designs and improves fuzzing harnesses for C/C++ and Rust. Covers mapping raw bytes onto a target API, generating structured inputs, avoiding non-determinism and false crashes, and deciding what to fuzz together. Use when writing a first LLVMFuzzerTestOneInput or fuzz_target! harness, when a campaign finds nothing or reports crashes that will not reproduce, or when the target API needs structured rather than raw input.

Measures and interprets what a fuzzing campaign actually reaches, using llvm-cov, lcov, or a fuzzer's own coverage output. Covers baselining a new campaign, reading coverage reports, and turning uncovered regions into harness, seed, or dictionary work. Use when a fuzzer plateaus, when judging whether a harness is effective, after changing a harness, or when asking why some code is never reached.

Writes, reviews, and debugs property-based tests — Hypothesis, fast-check, proptest, jqwik, rapid, and Echidna or Medusa for Solidity invariants. Use whenever tests should cover a whole input domain instead of a hand-picked list of examples: encode/decode and serialize/deserialize pairs, parsers, canonicalizers and normalizers, validators, numeric and Decimal types, comparators and sort order, data structures, and smart-contract state invariants. Also use when adding cases to an existing @given, fast-check, or proptest suite, when judging whether existing property tests assert anything real, and when a generator has shrunk a counterexample and you need to tell a wrong property from a genuine bug. Not for coverage-guided binary fuzzing (libFuzzer, AFL), mutation-testing campaigns, static analysis, benchmarking, or end-to-end UI tests.

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.

Launch Loki Mode autonomous SDLC agent. Handles PRD-to-deployment with minimal human intervention. Invoke for multi-phase development tasks, bug fixing campaigns, or full product builds.

Draft conversion-focused marketing copy for landing pages, homepages, pricing pages, feature pages, and campaign assets. Use when creating first drafts from positioning and audience context. Output file-first drafts under scripts/marketing/<slug>/ with explicit proof and CTA requirements.

Improve existing marketing copy through structured editing passes for clarity, voice, proof, specificity, and conversion impact. Use after drafting copy for pages, emails, and campaign assets. Produce deterministic review artifacts under scripts/marketing/<slug>/.

Legacy fallback for high-level campaign PM structure. Prefer launch-strategy for launch execution and canonical Core 9 skills for channel work. Use this template when a generic campaign framework is explicitly needed.

Analyze marketing performance with key metrics, trend analysis, and optimization recommendations. Use when building performance reports, reviewing campaign results, analyzing channel metrics (email, social, paid, SEO), or identifying what's working and what needs improvement.