87 skills · sorted by relevance
Create engineering retrospectives from Git history, covering delivered changes, work patterns, test code ratios, and frequently changed files. Review individual contributions and improvement opportunities, save metrics, and compare results with earlier periods.
Explain how input features contribute to machine-learning predictions using SHAP. Select an explanation method and reference data, validate contributions against model outputs, and create charts for individual predictions or patterns across samples, including models with multiple outputs.
Turn routine resume duties into concise bullets that show real contributions. Use focused questions to uncover achievements, verify numbers and individual responsibilities, and describe scope or concrete changes when reliable performance figures are unavailable.
Get instructions for installing and reviewing the full ai-ready skill in Copilot CLI. This wrapper explains how to add the latest version, reload skills, and request repository preparation for AI contributions.
Review a week of engineering work using commit history, work patterns, and code quality measures. It tracks trends across retrospectives and breaks down each team member’s contributions, highlighting strengths and areas for growth.
Create, update, or review agentmemory skills using a shared format. It guides document structure, supporting files, and generated reference data so contributions follow consistent rules and stay aligned with the source code.
Analyzes marketing campaign data to compare channel contributions, find drop-offs before purchase, and calculate returns and acquisition costs. Uses five attribution models, which assign credit to customer interactions, with results available as readable summaries or JSON.
Answer NemoClaw maintainer questions using policy references covering issue and pull request assessment, labels, project fields, releases, and competing contributions. It explains the relevant rules in plain language through a read-only workflow.
Search arXiv papers by topic or paper ID, review authors and abstracts, and summarize contributions stated in the abstracts. Download selected papers or all search results as PDFs to build a local paper library.
Merge GitHub pull requests while preserving credit for the original contributors. Covers straightforward merges, conflict resolution, selective file inclusion, duplicate PR closure, and checks that confirm both attribution and working code after integration.
Expert en écosystème d'agents IA (plugins, extensions, thèmes, communauté, contributions, gouvernance)
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Create or revise skills shipped within the Hermes Agent repository. The guidance covers file placement, required metadata, clear procedures, platform checks, tests, and documentation updates so contributions follow the repository’s authoring standards.
Produces detailed HTML or Markdown reports on pull requests, branches, or large code contributions. It explains how the system works, ranks concrete findings, compares designs when needed, and recommends whether and how to merge the changes.
Track pull requests opened by a Paperclip instance, explain their purpose, and assess whether their latest changes are ready to merge. Dispatch preparation work for unresolved problems and publish an evidence-based report without merging anything.
Create an HTML defense deck for a field-study capstone, organizing survey methods, findings, contributions, and limitations for faculty reviewers. The template uses yellow paper, safety-pin illustrations, and handwritten-style text for a warm presentation.
Coordinate multiple AI agents for research, development, testing, and system analysis. It guides role assignment, communication structures, parallel and sequential tasks, shared memory, progress monitoring, and recovery, bringing separate contributions into reports or coordinated development workflows.
Maintain a Chinese independent developer project list by reviewing comments, issues, and pull requests. Check duplicate URLs and submission eligibility, add projects to the appropriate README, merge contributions, and reply with the listing result.
Take a pull request through repeated code review and fixes, verify that automated checks pass for the latest commit, and combine its changes into one commit when merging. Conflicts with the request’s goal require confirmation.
Draft commit messages, pull request titles and descriptions, and GitHub comments or reviews for Apache Airflow contributions. Follows project wording and AI attribution rules, and helps decide whether a change needs a release note.
Review open GitHub pull requests and issues to rank useful, lower-risk actions. Produce a prioritized report covering merge candidates, already-fixed issues, small fixes, branch verification, and contributor credit, with public comments drafted for approval.
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.
Draft self-assessments, peer reviews, and feedback for managers using concrete examples of work and collaboration. Organizes achievements around context, actions, and results, matches your writing voice, and flags sections that need more evidence or detail.
Prepare repository contributions by checking existing guidelines, related issues, branch naming rules, commit formats, and pull request templates. Organize changes into logical commits and assemble submissions that follow the project's documented contribution process.
Make resume achievements more specific by identifying useful numbers, such as workload, time saved, or revenue. Guided questions uncover measurable contributions, while conservative estimates and documented reasoning help describe experience when exact records are unavailable.