Results for “deduplication”

Deduplicating Training Data Makes Language Models Better

Use to find duplicate or repeated support conversations and produce a reviewable merge plan. Trigger for "find duplicate tickets", "customers contacting us twice about the same thing", deduplicating a helpdesk, cleaning up ticket volume, or measuring how much of your contact volume is the same issue submitted more than once.

Refactors duplicated code by extracting helper methods, shared abstractions, or reusable structures, with automated testing and commits after each extraction.

Systematic debugging — reproduce, read the error, isolate, hypothesize, fix, verify, document. Use when tracking down a bug, unexpected behavior, or test failure — including phrases like "this doesn't work", "why is this failing", or "help me debug".

4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.

Investigate a problem, log it to the debug changelog, cross-check past issues, and suggest a non-duplicate fix.

Reproduces failures, gathers evidence, tests hypotheses, fixes root causes, and adds regression coverage.

You are the debugger. You follow the scientific method: observe, hypothesize, test, conclude. You never guess-and-patch.

Complete WhatsApp management for OpenClaw agents: per-conversation memory (groups + DMs), unanswered message tracking, loop prevention, and multi-PA coordination. Use when: tracking conversation context, recalling past decisions, finding unanswered messages, or preventing echo/duplicate message loops.

Analyzes .NET test suites for duplicated boilerplate, copy-paste tests, and structural maintainability issues, producing a report with concrete before/after refactoring suggestions.

Debug Python: pdb REPL + debugpy remote (DAP).

Use when investigating a bug, runtime error, unexpected behavior, test failure, or crash. For systematic root cause analysis, error message interpretation, stack trace reading, reproduction steps, and targeted fixes. Activate when the user says "it's broken", "this doesn't work", "I'm getting an error", or "help me debug".

Diagnose and fix a bug through a disciplined reproduce, isolate, diagnose, fix, verify loop driven by evidence and one hypothesis at a time — not guesswork.

Demystifying CLIP Data

Autopsy a stuck project, extract salvageable artifacts, and route to a fresh start via $bootstrap-repo reset or new-repo bootstrap

Debug Python code interactively with pdb and debugpy, covering local breakpoints, post-mortem analysis, and remote attachment to running processes.

Refactors code by removing unused imports, variables, methods, redundant comments, and fixing formatting, with automatic test runs and commits after each step.

Debugging is the scientific method under time pressure.

补充上下文，用更简单、明确的中文重新解释。

Anti-distillation defense for employee Skills. Clean your skill files to look complete but with core proprietary knowledge neutralized. Use when user wants to protect trade secrets, sanitize forced knowledge transfers, or create safe-to-submit skill documents.

HTTP request smuggling and desynchronization testing. Use when front proxies, CDNs, or load balancers disagree with the origin on message framing (Content-Length vs Transfer-Encoding), on HTTP/2→HTTP/1 translation, or when exploring client-side desync via browser fetch pipelines.

Deconstruct vague business concepts into atomic-level clarity using Wittgenstein's language philosophy and Austrian economics.

Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.

Reduction is a trade, not an improvement.