'evidence-based' 검색 결과

Investigate a GitHub issue or reported problem, check whether it is a bug, and test a proof of concept. Explain the behavior changes and supporting evidence so the user can decide whether to proceed with the full fix.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking whether a reported issue is a real bug
• Testing a proposed fix before full implementation
• Comparing performance before and after a change

Provide shared writing guidance and journal requirements for other installed Nature skills. This supporting reference package covers manuscript structure, evidence-based claims, and journal-specific formats; it is used through another skill rather than as a standalone workflow.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Referencing shared guidance through a Nature writing skill
• Consulting journal-specific submission requirements
• Reviewing manuscript length and repeated claims

Reconstruct how an AI coding agent produced a feature, pull request, or report using local ax records. Connect sessions, commits, skills, and tool activity into an evidence-based sequence with key decisions, checks, and a repeatable recipe.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Tracing how a shipped feature was built
• Reconstructing development from a commit
• Finding the workflow behind work done on a known date

Understand a codebase before searching for bugs or vulnerabilities. This skill examines functions line by line, documents assumptions and state changes, and traces calls across modules to build an evidence-based picture of system behavior.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Understanding a codebase before a security audit
• Tracing data and state changes across function calls
• Documenting assumptions for an architecture review

Analyze Antigravity coding session artifacts to explain scope changes, repeated rework, and underlying causes. Produce an evidence-based report with confidence levels, prompt assessments, recurring problem areas, and prioritized recommendations for improving future development sessions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing sessions with repeated rework
• Separating scope changes from agent and codebase problems
• Finding files and subsystems associated with recurring friction

Structure an evidence-based comparison of shortlisted accounting packages using 57 fields for capabilities, costs, and evaluator judgments. Request empty templates in CSV, SQL DDL, JSON Schema, or Notion mapping while keeping the final decision with the business.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare a common comparison template for accounting packages
• Define shared tests for vendor demonstrations
• Organize quoted costs for first-year and three-year comparisons

Turns supplied AI agent evaluation results into reports that distinguish autonomous success, human-assisted success, failure, timeout, and invalid runs. Makes metric denominators, retries, timing, costs, and comparison conditions explicit to support evidence-based decisions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Separating autonomous and human-assisted success rates
• Reporting evaluations with retries and invalid runs
• Comparing agents or releases under matched conditions

Evaluate job offers by separating guaranteed pay, conditional bonuses, and estimated equity value. Compare terms, develop an evidence-based counteroffer, draft emails and call scripts, rehearse recruiter conversations, and prepare deadline extensions, acceptance, or decline messages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing pay and terms across job offers
• Drafting a counteroffer email
• Rehearsing a salary negotiation call

Evaluate whether a fine-tuned model is ready for release by checking training data, general capability loss, comparisons with the base model, and staged production rollout. Produces an evidence-based promotion or rejection report with one prioritized remedy when rejected.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Deciding whether to release a fine-tuned model
• Checking whether training reduced general capabilities
• Reassessing a model against updated reference evaluations

Turn past classrooms and chat history into a reusable personal skill for course creation. It examines varied examples, checks recurring patterns and exceptions, and asks for corrections before saving instructions that reflect the user's workflow and quality expectations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing patterns across past course creation
• Turning preferred workflows into reusable instructions
• Checking inferred preferences against examples

Review a set of GitHub issues against their full discussions and current code. Produce a table separating completed work, small fixes, design work, and deferred items, with evidence, confidence levels, and next actions for each issue.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review a batch of issues or an entire milestone
• Find issues already addressed by current code
• Separate small fixes from design work and deferred items

Review open pull requests against the actual release branch, inspect code changes and failed checks, and produce an evidence-based table recommending direct integration, selective reuse, deferral, or closure, with contributor credit.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing the open pull request queue
• Selecting contributions for an upcoming release
• Checking conflicts against a local release branch

Investigate software failures by reproducing the problem, reducing the failing example, and locating its root cause. Receive an evidence-based diagnosis that separates symptoms from causes, with fixes applied only when authorized.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating a crash
• Diagnosing intermittently failing tests
• Tracing incorrect output

Review and refine source-code comments and documentation attached to functions or other declarations. The skill removes redundant explanations, checks outdated TODOs, and preserves concise, evidence-based reasons and constraints that maintainers cannot readily infer from the code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Cleaning up redundant code comments
• Reviewing TODO and FIXME markers
• Checking documentation when changing code

Audit GitHub Actions workflows and run history to identify wasted automated checks and runner time. Get up to three evidence-based improvements aimed at reducing runtime or cost while preserving required validation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate long GitHub Actions runs
• Review CI costs and unnecessary workflow runs
• Improve caching and cancellation of overlapping runs

Audit GitHub Codespaces startup time and spending, then identify up to three evidence-based improvements to development containers, machine sizes, prebuilds, or idle timeouts, with validation results and expected impact.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating slow Codespaces startup
• Reviewing Codespaces spending
• Trimming unused development container components

Investigate high CPU usage in Java applications with Arthas. Identify busy threads, inspect method call paths, and produce an evidence-based diagnosis with specific methods to examine next.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating sudden CPU spikes in Java applications
• Finding busy threads behind slow application responses
• Narrowing down methods for further tracing

Assess a company’s management through public statements, delivered commitments, crisis decisions, and use of company funds. Produce evidence-based scores for integrity, strategy, capital allocation, and governance, alongside a verdict on long-term trust.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check whether executives delivered on past commitments
• Review acquisitions, buybacks, dividends, and new ventures
• Assess ownership, compensation, and related-party dealings

Inspect npm packages and dependency files for malicious installation scripts, credential theft, and self-spreading behavior. Use GuardDog scanning, source inspection, known-malicious version checks, and isolated execution to produce an evidence-based assessment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Vetting a new npm dependency before adoption
• Reviewing dependency files during code review
• Checking lockfiles against known-malicious versions

Diagnose oh-my-codex installation and skill discovery problems by checking configuration, hooks, plugin caches, and optional Team runtime checks. Produce an evidence-based report and carry out confirmed repairs with user approval, then verify the results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate installation or skill discovery failures
• Check for duplicate hooks and legacy settings
• Inspect plugin cache version conflicts

Audit deployed Vercel projects for cost and performance improvements using production metrics. Examines usage, settings, and relevant code, then produces ranked recommendations supported by verified files and documentation matching the framework version.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate Vercel usage and cost drivers
• Find routes with measured performance problems
• Assess caching opportunities using traffic data

Have a different AI model review code, analysis, or documents against the original skill's stated requirements. Receive evidence-based findings and a comparison of agreement and disagreement, then decide which recommendations to accept.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Getting a second opinion on substantial code changes
• Reviewing authentication and other security-sensitive changes
• Checking work before a bulk operation

Investigate slow jobs, stale data, and timeout alerts by timing the specific operation and comparing monitoring thresholds. Produce an evidence-based verdict that distinguishes insufficient time, stalled work, and false alerts before proposing changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate repeated timeout alerts
• Check whether stale-data warnings reflect actual lag
• Compare monitor thresholds with gbrain doctor

Research sales accounts using Common Room data to summarize company details, buying signals, ownership, and key contacts. Answer specific questions directly or prepare a broader briefing with evidence-based next steps, clearly identifying missing information.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare a company briefing before a sales conversation
• Check buying signals and recent account activity
• Find account owners and key contacts