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Found 666 Skills
6-phase investigation workflow for understanding existing systems. Auto-activates for research tasks. Optimized for exploration and understanding, not implementation. Includes parallel agent deployment for efficient deep dives and automatic knowledge capture to prevent repeat investigations.
Use this when the user explicitly requests to "verify/optimize in-text citations of the `{topic}_review.tex` review" or to "run check-review-alignment". Use the host AI's semantic understanding to verify each citation against the literature content one by one. **Only when fatal citation errors are found**, make minimal rewrites to the "sentences containing citations", and reuse the rendering script of `systematic-literature-review` to output PDF/Word (the script does not directly call the LLM API locally). Core principle: **Do not modify for the sake of modifying**. When it is uncertain whether it is a fatal error, keep the original content and issue a warning in the report. ⚠️ Not applicable in the following cases: - The user only wants to generate the main body of a systematic review (should use systematic-literature-review) - The user only wants to add/verify BibTeX entries (should use a dedicated bib management process)
Use when building anything non-trivial. Enforces a spec → plan → execute → verify loop that prevents "looks right" failures. Creates spec.md, todo.md, and decisions.md before writing code.
Set up or log in to Karma. Use when user says "set up agent", "configure API key", "connect to Karma", "login to Karma", "log in", or before first use of any Karma skill.
Guide for creating AI subagents with isolated context for complex multi-step workflows. Use when users want to create a subagent, specialized agent, verifier, debugger, or orchestrator that requires isolated context and deep specialization. Works with any agent that supports subagent delegation. Triggers on "create subagent", "new agent", "specialized assistant", "create verifier".
Iterative execution methodology. Small steps, verify each, adapt based on results.
An Agent dedicated to brainstorming and finalizing specifications. Finalize a single, implementable and testable Spec.md.
Comprehensive Go backend code review with optional parallel agents
Create detailed, execution-ready implementation plans for complex or high-risk changes without coding. Use when scope is large, requirements are mostly known, and work should be broken into validated phases before execution.
Looks up phone number details via Sinch Number Lookup API. Use when checking carrier, line type, porting status, SIM swap, VoIP detection, or reassigned number detection (RND) for fraud prevention or routing decisions.
Use when you need maximum precision on a critical task — production deployments, security-sensitive code, financial calculations, or any work where mistakes are unacceptable.
Process external code review feedback with technical rigor. Use when receiving feedback from another LLM, human reviewer, or CI tool. Verifies claims before implementing, tracks disposition.