Audit Go, Python, or TypeScript code for over-engineering — duplication, reinvented primitives, unnecessary abstractions, dead code paths, over-parameterized APIs, mixed concerns, complex control flow, coexisting generations. Defaults to the codebase.
Audit Go, Python, or TypeScript code for code smells — feature envy, data clumps, shotgun surgery, temporal coupling, primitive obsession, god modules, global state, anemic models, class abuse. Defaults to the codebase.
Act as a senior Go engineer performing a critical design and testing review. Evaluates architecture, patterns, idiomaticity, over-engineering, testing strategy, and proposes concrete improvements — all grounded in the codebase. Use when: reviewing a Go codebase for design soundness, testing robustness, or overall code…
Grilling session that challenges your requirements against the existing codebase. Reports omit empty sections — no placeholder headings, empty tables, or negative statements like "no issues found".
Clarify the user’s intent for vague, incomplete, or ambiguous clauses, statements, and requirements before modifying the code. Reports omit empty sections — no placeholder headings, empty tables, or negative statements like "no issues found".
Audit Go code for missing documentation where the "why" is not obvious — obscure calculations, non-trivial business rules, surprising behavior, implicit constraints, workarounds, and missing godoc on exported symbols. Finds where a comment would save the next reader significant time. Use when: reviewing Go code for…
Run all 10 Go code quality hunters in parallel as subagents and write each report to a timestamped reports folder. Covers boundary, doc, invariant, security, simplicity, slop, smell, solid, test, and type hunters. Use when: running a full Go codebase audit, scanning all quality dimensions at once, preparing for a code…
Audit Go test code for quality gaps — missing coverage on critical paths, brittle tests coupled to implementation, over-mocking, assertion-free tests, missing edge cases, table-driven test misuse, and race condition blindness. Focuses on test effectiveness. Use when: reviewing Go test suites for reliability, reducing…
Audit Python code for missing or misleading inline documentation where the "why" is not obvious — obscure calculations, non-trivial business rules, surprising behavior, implicit constraints, workarounds, and stale comments that contradict the current code. Finds where a comment would save the next reader significant…
Run all 12 Python code quality hunters in parallel as subagents and write each report to a timestamped reports folder. Covers boundary, doc, error, invariant, perf, security, simplicity, slop, smell, solid, test, and type hunters. Use when: running a full Python codebase audit, scanning all quality dimensions at once…
Audit Python test code for quality gaps — missing coverage on critical paths, brittle tests coupled to implementation, over-mocking, assertion-free tests, missing edge cases, and duplicated test setup. Focuses on test effectiveness, not production code structure. Use when: reviewing Python test suites for reliability…
Audit TypeScript code for missing inline documentation where the "why" is not obvious — obscure calculations, non-trivial business rules, surprising behavior, implicit constraints, and workarounds. Finds where a comment would save the next reader significant time. Use when: reviewing TypeScript code for long-term…
Run all 12 TypeScript code quality hunters in parallel as subagents and write each report to a timestamped reports folder. Covers boundary, doc, error, invariant, perf, security, simplicity, slop, smell, solid, test, and type hunters. Use when: running a full TypeScript codebase audit, scanning all quality dimensions…
Audit TypeScript test code for quality gaps — missing coverage on critical paths, brittle tests coupled to implementation, over-mocking, assertion-free tests, missing edge cases, and duplicated test setup. Focuses on test effectiveness, not production code structure. Use when: reviewing TypeScript test suites for…
Transforms vague feature ideas into precise, codebase-grounded technical requirements. Use when requirements are ambiguous/incomplete, the user struggles to describe behavior, terminology is unclear, or multiple concepts are mixed. Output is a requirements spec—NOT an implementation plan. Reports omit empty sections …
Use when an LLM-facing document — a prompt, skill file, spec, or instruction set — is verbose and must fit a tighter token budget. Not for user-facing copy, legal text, changelogs, or quoted material.
★not rated 5 yesterdayA53 tokens
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: