Install
$ agentstack add skill-however-yir-claude-skills-java-fullstack-engineering ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Java Fullstack Engineering
Use this skill when the task is primarily about shipping, fixing, hardening, or explaining a Java full-stack project rather than exploring AI workflows or producing presentation materials.
This skill is optimized for projects like campus systems, management backends, recommendation platforms, and Spring Boot plus frontend applications. It keeps the work grounded in engineering quality: correctness, maintainability, API clarity, database safety, and verification.
Inputs
Useful inputs for this skill include:
- repository or module context
- stack details such as Spring Boot, MyBatis, JPA, Vue, React, MySQL, Redis
- bug reports, failing behavior, stack traces, or screenshots
- performance symptoms such as slow SQL, slow endpoints, or heavy pages
- API contracts, schema notes, or interview-presentation goals
Outputs
Strong outputs from this skill usually include:
- a focused code or config change
- a short explanation of the behavior change
- engineering reasoning for the chosen approach
- verification notes such as tests, build status, or manual checks
- remaining risks, edge cases, or follow-up suggestions
Non-goals
This skill is not the best fit for:
- purely visual frontend polish with no engineering depth
- broad AI workflow architecture or prompt-system design
- marketing copy, slides, or portfolio packaging as the primary task
- vague ideation without a concrete codebase or engineering target
Workflow
- Orient quickly.
Read the entry files, stack files, and affected slice before proposing changes. Prefer rg, focused file reads, and config inspection over guessing.
- Identify the engineering axis.
Classify the task as one or more of:
- business logic or bug fix
- API or controller contract
- persistence or SQL
- performance or caching
- frontend integration
- test gap
- project hardening for interview or production readiness
- Apply the right depth.
For simple fixes, change the smallest safe surface. For medium tasks, explain the behavior change and verify with targeted commands. For bigger refactors, keep a clear boundary and avoid mixing unrelated cleanups.
- Verify the result.
Whenever possible:
- run the narrowest relevant test
- compile or lint the touched module
- inspect SQL, API responses, or logs if behavior depends on data flow
- call out anything you could not verify
Examples
Example 1: Spring Boot bug fix
User request: > Help me fix this Spring Boot login bug. The controller returns 200 but the frontend still thinks auth failed.
Good use of this skill:
- inspect controller, service, DTO, and frontend caller together
- verify response shape and error handling contract
- patch the smallest safe surface
- explain the user-facing fix and verification status
Example 2: SQL and API cleanup
User request: > Clean up these REST APIs and optimize the recruitment list query.
Good use of this skill:
- review controller naming, request parameters, DTO boundaries, and mapper SQL
- identify N+1 or poor index usage
- tighten response consistency and query performance together only where they are coupled
Example 3: Interview-grade hardening
User request: > Make this campus recruitment recommendation system look more production-ready for interviews.
Good use of this skill:
- surface architecture strengths already present
- strengthen validation, error handling, test coverage, and API clarity
- avoid fake complexity and keep claims tied to real code evidence
Pairing With Other Skills
Use these when the task naturally narrows:
code-reviewerfor bug risk and regression reviewperformance-profilerfor slow interfaces, SQL, or renderingqa-expertfor tests and edge casesapi-design-reviewerfor controller and contract cleanupdatabase-designerfor schema, index, and relation workobservability-designerfor logs, metrics, tracing, and alertingast-grepandcodegraphfor large refactors or codebase understanding
Triggers
Common requests that should trigger this skill:
- "Help me fix this Spring Boot bug"
- "Refactor this Java backend"
- "Optimize this MySQL query"
- "Clean up these REST APIs"
- "Review this campus recruitment recommendation system"
- "Make this project more interview-ready"
Reference
Read [references/checklist.md](references/checklist.md) when you need a compact implementation and review checklist.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: however-yir
- Source: however-yir/claude-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.