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Agent skill

Sentry Issue Fixer

by genlayerlabs in genlayerlabs/genlayer-studio

Fetch, analyze, fix Sentry issues, run tests, and create PRs

MITAuto-check passedTesting & QA

Install Sentry Issue Fixer

skills CLI
$ npx skills add genlayerlabs/genlayer-studio --skill sentry-issue-fixer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install genlayerlabs/genlayer-studio sentry-issue-fixer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/genlayerlabs/genlayer-studio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/sentry-issue-fixer .claude/skills/sentry-issue-fixer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
sentry-issue-fixer
GitHub stars
180
Token cost
~2k tokens
SKILL.md length
502 words
Files
1
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Fetch, analyze, fix Sentry issues, run tests, and create PRs

  • Works in 7 steps: Fetch Most Important Open Issue → Analyze the Issue → Plan the Fix → …
  • Tasks that involve MCP servers
  • SKILL.md covers Prerequisites, MCP Server Configuration, Workflow and Sentry MCP Tools Reference, plus 3 more sections
  • Calls git, docker and pytest; reaches mcp.sentry.dev

What it does

Sentry Issue Fixer is an agent skill from genlayerlabs/genlayer-studio. Fetch, analyze, fix Sentry issues, run tests, and create PRs

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Testing & QA, covering MCP servers. It works with Sentry, Model Context Protocol and Docker. The repository describes itself as: An interactive sandbox to explore the GenLayer Protocol. The licence is MIT.

When your agent uses it

  • Tasks that involve MCP servers

Example prompts

  • “/sentry-issue-fixer”

Requirements

  • Python 3
  • Docker

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Fetch Most Important Open Issue
  2. Analyze the Issue
  3. Plan the Fix
  4. Implement the Fix
  5. Run ALL Test Suites
  6. Run Integration Tests (Optional - if Docker services are running)
  7. Create Pull Request

What it can do on your machine

Read from SKILL.md and the folder at commit c940729. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git
    • docker
    • pytest
    • npm
    • gh

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • mcp.sentry.dev

    Also links to:

    • docs.sentry.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Sentry Issue Fixer loads about 2k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 502 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from genlayerlabs/genlayer-studio at commit c940729, republished under its MIT licence (© genlayerlabs). 502 words, ~2,048 tokens.

Download SKILL.mdSave it as .claude/skills/sentry-issue-fixer/SKILL.md (or your agent's skills folder).
name
sentry-issue-fixer
description
Fetch, analyze, fix Sentry issues, run tests, and create PRs
invocation
user

Sentry Issue Fixer

Automatically fetch the most important open Sentry issue, analyze it, implement a fix, verify with tests, and create a pull request.

Prerequisites

  • Sentry MCP server connected (configured in ~/.claude/settings.json)
  • GitHub CLI (gh) authenticated
  • Docker running (for integration tests)
  • Python 3.12 with virtualenv
  • Checkout main branch and pull the latest changes

MCP Server Configuration

The Sentry MCP server should be configured in ~/.claude/settings.json:

json
{
  "mcpServers": {
    "Sentry": {
      "url": "https://mcp.sentry.dev/mcp"
    }
  }
}

On first use, you'll be prompted to authenticate with Sentry via OAuth.

Workflow

Step 1: Fetch Most Important Open Issue

Use Sentry MCP tools to get the highest priority unresolved issue:

1. First, list available organizations:
   mcp__Sentry__list_organizations

2. List projects in the organization:
   mcp__Sentry__list_projects with organization_slug

3. Search for unresolved issues sorted by priority/frequency:
   mcp__Sentry__search_issues with:
   - organization_slug
   - project_slug
   - query: "is:unresolved"
   - sort: "freq" or "priority"

4. Get detailed issue information:
   mcp__Sentry__get_issue with issue_id
Step 2: Analyze the Issue

Use Sentry's analysis tools:

1. Get issue details and stack trace:
   mcp__Sentry__get_issue_details

2. Find errors in specific files:
   mcp__Sentry__find_errors_in_file with filename from stack trace

3. Use Seer AI for root cause analysis (if available):
   mcp__Sentry__invoke_seer_agent for AI-powered fix suggestions

Gather from analysis:

  • Exception type and message
  • Stack trace (file, function, line number)
  • Error frequency and affected users
  • Environment context (tags, release, etc.)
  • Pattern of occurrences
Step 3: Plan the Fix

Before implementing, create a plan:

  1. Root Cause Analysis

    • What is causing the error?
    • Is it a logic error, missing validation, race condition, etc.?

  2. Proposed Solution

    • What changes are needed?
    • Which files need modification?
    • Are there related issues to consider?

  3. Risk Assessment

    • Could this fix break other functionality?
    • Does it need backward compatibility?

  4. Testing Strategy

    • What unit tests should be added/modified?
    • What integration tests are relevant?
Step 4: Implement the Fix

  1. Create a Feature Branch

    bash
    git checkout main
git pull origin main
git checkout -b fix/sentry-<issue-id>-<short-description>

  2. Make Code Changes

    • Implement the planned fix
    • Add appropriate error handling
    • Add or update tests

  3. Commit Changes

    bash
    git add <files>
git commit -m "fix: <description>

Fixes Sentry issue <issue-id>

Co-Authored-By: Claude <noreply@anthropic.com>"
Step 5: Run ALL Test Suites

IMPORTANT: You MUST run ALL of the following test suites before creating a PR. Do NOT skip any.

5.1 DB/SQLAlchemy Tests (Primary Backend Tests - Dockerized)
bash
docker compose -f tests/db-sqlalchemy/docker-compose.yml --project-directory . run --build --rm tests
5.2 Backend Unit Tests
bash
.venv/bin/pytest tests/unit/ -v --tb=short --ignore=tests/unit/test_rpc_endpoint_manager.py
5.3 Frontend Unit Tests
bash
cd frontend && npm run test

If any tests fail:

  • Analyze the failure
  • Fix the issue
  • Re-run ALL test suites until they pass
Show full SKILL.md (212 more words)Show less
Step 6: Run Integration Tests (Optional - if Docker services are running)

Follow the integration-tests skill:

bash
# Ensure Docker is running with the studio
docker compose ps  # Verify services are up

source .venv/bin/activate
export PYTHONPATH="$(pwd)"

# Run integration tests in parallel (excluding test_validators.py)
gltest --contracts-dir . tests/integration -n 4 --ignore=tests/integration/test_validators.py

# Run validator tests separately
gltest --contracts-dir . tests/integration/test_validators.py

If tests fail:

  • Check Docker logs: docker compose logs -f
  • Analyze test output
  • Fix issues and re-run
Step 7: Create Pull Request

Follow the create-pr skill:

bash
# Push branch
git push -u origin $(git branch --show-current)

# Create PR with Sentry context
gh pr create --title "fix: <description from Sentry issue>" --body "$(cat <<'EOF'
Fixes Sentry issue: <link-to-sentry-issue>

# What

- [Describe the error that was occurring]
- [List the changes made to fix it]

# Why

- This error was affecting [X users / occurring Y times]
- Root cause: [explanation]

# Testing done

- [x] Unit tests pass
- [x] Integration tests pass
- [x] Verified fix resolves the Sentry error pattern

# Decisions made

- [Document any non-obvious choices]

# Checks

- [x] I have tested this code
- [x] I have reviewed my own PR
- [x] I have set a descriptive PR title compliant with conventional commits

# Reviewing tips

- Focus on [specific areas]
- The main change is in [file/function]

# User facing release notes

- Fixed: [user-visible description of what was broken]
EOF
)"

Sentry MCP Tools Reference

Based on Sentry MCP documentation (https://docs.sentry.io/product/sentry-mcp/):

CategoryTools
CoreOrganizations, Projects, Teams, Issues, DSNs
AnalysisError Searching, Issue Analysis, Seer Integration
AdvancedRelease Management, Performance Monitoring, Custom Queries
Common Tool Patterns
# List organizations you have access to
mcp__Sentry__list_organizations

# List projects in an organization
mcp__Sentry__list_projects(organization_slug)

# Search for issues
mcp__Sentry__search_issues(organization_slug, query="is:unresolved")

# Get issue details
mcp__Sentry__get_issue(issue_id)

# Find errors in a specific file
mcp__Sentry__find_errors_in_file(organization_slug, project_slug, filename)

# Use Seer AI agent for analysis
mcp__Sentry__invoke_seer(issue_id)

Common Issue Patterns

Error TypeTypical Fix
NoneType errorsAdd null checks, validate inputs
KeyErrorCheck dict key existence, use .get()
Timeout errorsAdd retry logic, increase timeout
Connection errorsAdd error handling, retry with backoff
Validation errorsImprove input validation, add type hints

Example Session

1. List organizations:
   > mcp__Sentry__list_organizations
   Result: [{"slug": "genlayer", ...}]

2. Search unresolved issues:
   > mcp__Sentry__search_issues(org="genlayer", query="is:unresolved", sort="freq")
   Result: Top issue: "KeyError: 'validator_address' in consensus/worker.py"

3. Get issue details:
   > mcp__Sentry__get_issue(issue_id="12345")
   Result: Stack trace showing error at worker.py:145

4. Analyze:
   - Error in worker.py:145 accessing result['validator_address']
   - Occurs when validator response is incomplete
   - 47 events, affecting 12 users

5. Plan:
   - Add validation before accessing key
   - Log warning for incomplete responses
   - Add unit test for edge case

6. Implement:
   - Edit worker.py to add .get() with default
   - Add test_worker_missing_validator_address test

7. Test:
   - gltest --contracts-dir . tests/unit/test_worker*.py
   - All pass

8. Create PR:
   - gh pr create with Sentry context

Troubleshooting

Sentry MCP Not Connected
  • Restart Claude Code to trigger OAuth flow
  • Check ~/.claude/settings.json has the mcpServers configuration
  • Verify you have access to the Sentry organization
Cannot Find Issues
  • Check organization and project slugs are correct
  • Verify you have the right permissions in Sentry
  • Try different query filters (is:unresolved, is:unhandled)
Cannot Reproduce Issue Locally
  • Check environment differences (env vars, config)
  • Use Sentry event data to understand exact conditions
  • Add logging to capture more context
Tests Timeout
  • Use --leader-only for faster integration tests
  • Run specific test files instead of full suite

© genlayerlabs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/sentry-issue-fixer of genlayerlabs/genlayer-studio.

Open the folder on GitHubat commit c940729

Compare with similar skills

Sentry Issue Fixer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Sentry Issue Fixer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Sentry Issue Fixer this skillgenlayerlabs/genlayer-studio180—~2kAutomated safety check: PassMIT
Sonar CoverageSonarSource/sonarqube-agent-plugins111—~2.1kAutomated safety check: PassCustom licence
Sonarqube MCPgiuseppe-trisciuoglio/developer-kit355—~3.3kAutomated safety check: PassMIT
Dotnet Debuggingnovotnyllc/dotnet-artisan233—~2.1kAutomated safety check: PassMIT
Project Releaseswimmwatch/cloakbrowser-mcp161—~1.9kAutomated safety check: PassMIT
Project Pull Requestswimmwatch/cloakbrowser-mcp161—~1kAutomated safety check: PassMIT

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Works with

Categories

Questions about Sentry Issue Fixer

What does Sentry Issue Fixer do?

Fetch, analyze, fix Sentry issues, run tests, and create PRs. Sentry Issue Fixer is an agent skill from genlayerlabs/genlayer-studio.

When should I use Sentry Issue Fixer?

Sentry Issue Fixer fits situations like: tasks that involve MCP servers.

How do I install Sentry Issue Fixer in Claude Code?

Run `npx skills add genlayerlabs/genlayer-studio --skill sentry-issue-fixer -a claude-code`. Or copy the skill folder (.claude/skills/sentry-issue-fixer in genlayerlabs/genlayer-studio) into .claude/skills/sentry-issue-fixer in your project. Claude Code loads it when a task matches its description.

How do I install Sentry Issue Fixer in Codex?

Run `npx skills add genlayerlabs/genlayer-studio --skill sentry-issue-fixer -a codex`. Or copy the skill folder (.claude/skills/sentry-issue-fixer in genlayerlabs/genlayer-studio) into .agents/skills/sentry-issue-fixer in your project. Codex loads it when a task matches its description.

Can I use Sentry Issue Fixer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add genlayerlabs/genlayer-studio --skill sentry-issue-fixer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sentry-issue-fixer, .gemini/skills/sentry-issue-fixer, .github/skills/sentry-issue-fixer and .opencode/skills/sentry-issue-fixer in your project.

What does Sentry Issue Fixer need to run?

Going by SKILL.md and its folder, Sentry Issue Fixer needs the command-line tools its instructions call (git, docker, pytest, npm and gh). Our summary lists: Python 3; Docker.

Does Sentry Issue Fixer access the network?

SKILL.md names 2 domains. In commands or code: mcp.sentry.dev; the agent is likely to contact it when it follows the instructions. As links in the text: docs.sentry.io. This is read from the text; nothing was executed.

Is Sentry Issue Fixer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Sentry Issue Fixer use?

Sentry Issue Fixer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Sentry Issue Fixer use?

About 2k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Sentry Issue Fixer?

Skills that share tags, products or a category with Sentry Issue Fixer: Sonar Coverage (SonarSource/sonarqube-agent-plugins, 111 stars), Sonarqube MCP (giuseppe-trisciuoglio/developer-kit, 355 stars), Dotnet Debugging (novotnyllc/dotnet-artisan, 233 stars) and Project Release (swimmwatch/cloakbrowser-mcp, 161 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Sentry Issue Fixer?

genlayerlabs (a GitHub organization) maintains it in genlayerlabs/genlayer-studio, which has 180 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 7, 2026.

Source: genlayerlabs/genlayer-studio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.