Platform Integration (GitHub/GitLab)
This skill should be used when the user asks to "fetch GitHub issue", "get GitLab issue", "analyze GitHub PR", "search GitHub repo", "check GitLab commits", "use GitHub API", "use GitLab API", or mentions fetching data from GitHub or GitLab for incident investigation. Provides guidance for integrating with GitHub and GitLab APIs for RCA.
What this skill does
# Platform Integration (GitHub/GitLab)
## Overview
GitHub and GitLab are popular code hosting platforms that also track issues, pull requests, and commits. This skill provides guidance for fetching and analyzing data from these platforms during root cause analysis, particularly when production issues are reported via GitHub/GitLab issues.
## When to Use This Skill
Apply this skill when:
- Analyzing GitHub or GitLab issues reporting production problems
- Fetching commit history for affected code
- Using git blame to identify code authors
- Searching repositories for error-related code
- Correlating issues with pull requests or merges
- Tracking who made changes related to incidents
## Platform Similarities and Differences
Both GitHub and GitLab provide similar capabilities:
- Issue tracking
- Pull/Merge request management
- Repository hosting
- Commit history and blame
- Code search
- API access
**Key differences**:
- **GitHub**: Uses "Pull Requests" (PRs)
- **GitLab**: Uses "Merge Requests" (MRs)
- **API endpoints**: Different base URLs and authentication
- **Issue references**: GitHub uses `#123`, GitLab uses `!123` for MRs
This skill covers both platforms; adapt examples to your platform of choice.
## Authentication
### GitHub Personal Access Token
Create token at: https://github.com/settings/tokens
**Required scopes**:
- `repo` - Full repository access (includes issues, commits, code)
- `read:org` - Read organization data (if using org repos)
**Usage in API calls**:
```
Authorization: Bearer ghp_yourtoken
```
### GitLab Personal Access Token
Create token at: https://gitlab.com/-/profile/personal_access_tokens
**Required scopes**:
- `api` - Full API access
- `read_repository` - Read repository data
**Usage in API calls**:
```
Authorization: Bearer glpat_yourtoken
```
**Configure in Thufir settings** (`.claude/thufir.local.md`):
```yaml
github:
token: "ghp_your_token_here"
default_repo: "owner/repository"
gitlab:
token: "glpat_your_token_here"
default_project: "group/project"
```
## Working with Issues
### Fetching Issue Details
**GitHub API**:
```
GET /repos/{owner}/{repo}/issues/{issue_number}
```
**GitLab API**:
```
GET /projects/{id}/issues/{issue_iid}
```
### Issue Structure
Issues contain:
- **Title**: Brief description
- **Body/Description**: Detailed description, often includes error logs
- **Labels**: Tags like "production", "incident", "bug"
- **State**: open, closed
- **Created/Updated timestamps**
- **Comments**: Discussion and updates
- **Assignees**: Who's working on it
### Extracting RCA Information
From issue body, extract:
- **Error messages**: Search for stack traces, error codes
- **Reproduction steps**: How to trigger the issue
- **Affected features**: Which part of the system broke
- **Time of occurrence**: When users first noticed
- **User impact**: How many users affected
**Example parsing**:
```
Issue body:
"Users are getting 500 errors when trying to log in.
Error: ConnectionPoolExhausted at 2025-12-19 14:32 UTC
Approximately 15,000 users affected."
Extracted:
- Error: ConnectionPoolExhausted
- Time: 2025-12-19 14:32 UTC
- Impact: 15,000 users
- Feature: Login
```
### Filtering Issues
**GitHub - List issues with labels**:
```
GET /repos/{owner}/{repo}/issues?labels=production,incident&state=open
```
**GitLab - List issues with labels**:
```
GET /projects/{id}/issues?labels=production,incident&state=opened
```
## Commit Analysis
### Fetching Recent Commits
**GitHub - List commits**:
```
GET /repos/{owner}/{repo}/commits?since=2025-12-19T00:00:00Z
```
**GitLab - List commits**:
```
GET /projects/{id}/repository/commits?since=2025-12-19T00:00:00Z
```
### Commit Information
Each commit includes:
- **SHA**: Unique identifier
- **Message**: Commit description
- **Author**: Name and email
- **Timestamp**: When committed
- **Files changed**: List of modified files
- **Diff**: Changes made
### Finding Relevant Commits
Filter commits by:
1. **Time range**: Commits before incident start
2. **Files**: Commits touching affected files
3. **Author**: Specific developer
4. **Message content**: Keywords like "fix", "update", "config"
### Using Git Blame
Git blame identifies who last modified each line.
**GitHub - Get blame**:
```
GET /repos/{owner}/{repo}/blame/{ref}/{path}
```
**GitLab - Get blame**:
```
GET /projects/{id}/repository/files/{path}/blame?ref=main
```
**Parse blame output** to find:
- Line number
- Commit SHA
- Author
- Timestamp
- Original code
**Use for RCA**:
- Identify who changed problematic code
- Find when change was introduced
- Trace back to original commit
## Code Search
### Searching for Error Messages
**GitHub - Search code**:
```
GET /search/code?q=ConnectionPoolExhausted+repo:owner/repo
```
**GitLab - Search in project**:
```
GET /projects/{id}/search?scope=blobs&search=ConnectionPoolExhausted
```
### Search Strategies
**Search for error strings**:
- Remove variable parts: `ConnectionPoolExhausted` not `ConnectionPoolExhausted: timeout=5000ms`
- Search exact phrases with quotes: `"Could not acquire connection"`
- Use AND/OR for multiple terms
**Search for code patterns**:
- Function names from stack traces
- Class names
- Configuration keys
- API endpoint paths
**Example RCA search workflow**:
1. Extract error from issue: `ConnectionPoolExhausted`
2. Search code for error string
3. Find where error is raised
4. Use blame to identify recent changes
5. Review commits for root cause
## Pull/Merge Request Analysis
### Fetching PR/MR Details
**GitHub - Get pull request**:
```
GET /repos/{owner}/{repo}/pulls/{pr_number}
```
**GitLab - Get merge request**:
```
GET /projects/{id}/merge_requests/{mr_iid}
```
### PR/MR Information
Includes:
- **Title and description**
- **Author**
- **Created/merged timestamps**
- **Files changed**
- **Diff**: Code changes
- **Commits**: List of commits in the PR/MR
- **Status**: open, merged, closed
### Correlating Issues with PRs/MRs
**Link issues to PRs**:
- PR descriptions often reference issues: "Fixes #123"
- GitHub automatically links PRs that fix issues
- Check if incident-related issue has linked PRs
**Identify problematic merge**:
- Find PRs merged around incident time
- Check PRs that modified affected files
- Review PRs from specific authors
## Integration with Thufir MCP
Thufir provides MCP servers for GitHub and GitLab:
### GitHub MCP Tools
**get_issue**:
- Fetch issue by number
- Returns title, body, labels, timestamps
**list_commits**:
- List commits in time range
- Filter by path, author
**get_blame**:
- Get blame for specific file
- Identify line authors
**search_code**:
- Search repository for code patterns
- Find error strings in codebase
### GitLab MCP Tools
**get_issue**:
- Fetch issue by IID
- Returns description, labels, timestamps
**list_commits**:
- List commits with filters
- Since/until time range
**get_blame**:
- Get blame for file path
- Identify code authors
**search_code**:
- Search project blobs
- Find error patterns
### Using MCP for RCA
**Workflow example**:
1. **Fetch issue details**:
```
Use MCP: github_get_issue
Parameters: issue_number=456
Result: Issue describes login failures at 14:32 UTC
```
2. **Extract error and search code**:
```
Use MCP: github_search_code
Parameters: query="ConnectionPoolExhausted"
Result: Found in src/config/database.js
```
3. **Get blame for suspicious file**:
```
Use MCP: github_get_blame
Parameters: path="src/config/database.js"
Result: Line 45 changed by Developer X in commit abc123
```
4. **List recent commits**:
```
Use MCP: github_list_commits
Parameters: since="2025-12-19T00:00:00Z", path="src/config/database.js"
Result: Commit abc123 at 10:15 UTC changed pool size
```
## Best Practices
### Issue Analysis
- Read full issue body, not just title
- Check comments for additional context
- Look for error logs in code blocks
- Note timestamps in issue description
- Check for related/duplicate issues
### Commit Investigation
- FoRelated in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.