external/trailofbits-skills-curated/plugins/openai-gh-fix-ci/skills/openai-gh-fix-ci/SKILL.md
Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL. Originally from OpenAI's curated skills catalog.
npx skillsauth add seikaikyo/dash-skills openai-gh-fix-ciInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use gh to locate failing PR checks, fetch GitHub Actions logs for actionable failures, summarize the failure snippet, then propose a fix plan and implement after explicit approval.
create-plan) is available, use it; otherwise draft a concise plan inline and request approval before implementing.Prereq: authenticate with the standard GitHub CLI once (for example, run gh auth login), then confirm with gh auth status (repo + workflow scopes are typically required).
repo: path inside the repo (default .)pr: PR number or URL (optional; defaults to current branch PR)gh authentication for the repo hostpython "{baseDir}/scripts/inspect_pr_checks.py" --repo "." --pr "<number-or-url>"--json if you want machine-friendly output for summarization.gh auth status in the repo.gh auth login (ensuring repo + workflow scopes) before proceeding.gh pr view --json number,url.python "{baseDir}/scripts/inspect_pr_checks.py" --repo "." --pr "<number-or-url>"--json for machine-friendly output.gh pr checks <pr> --json name,state,bucket,link,startedAt,completedAt,workflow
gh.detailsUrl and run:
gh run view <run_id> --json name,workflowName,conclusion,status,url,event,headBranch,headShagh run view <run_id> --loggh api "/repos/<owner>/<repo>/actions/jobs/<job_id>/logs" > "<path>"detailsUrl is not a GitHub Actions run, label it as external and only report the URL.create-plan skill to draft a concise plan and request approval.gh pr checks to confirm.Fetch failing PR checks, pull GitHub Actions logs, and extract a failure snippet. Exits non-zero when failures remain so it can be used in automation.
Usage examples:
python "{baseDir}/scripts/inspect_pr_checks.py" --repo "." --pr "123"python "{baseDir}/scripts/inspect_pr_checks.py" --repo "." --pr "https://github.com/org/repo/pull/123" --jsonpython "{baseDir}/scripts/inspect_pr_checks.py" --repo "." --max-lines 200 --context 40tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.