Install
$ agentstack add skill-aditikilledar-hooligan-harness-hooligan-harness ✓ 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
Objective
To replace one-shot code generation with a structured, self-correcting agentic loop that ensures all code is planned in YAML, implemented via best practices of coding, and verified by an adversarial evaluator before declared complete.
Instructions
1. Phase 0: Initialization
- Read the repository README.md to understand the environment.
- Create .harness/dev_init.md with instructions to run the development server for downstream agents.
2. Phase 1: Planning (The Planner)
- Create a technical roadmap at .harness/[nickname].yaml.
- Define specific, quantifiable Acceptance Criteria (AC) for every task.
- Initialize an append-only log at .harness/progress.md to track all session activity.
3. Phase 2: Implementation (The Generator)
- Select Task: Identify the next pending task based on depends_on logic.
- Logic Synthesis: Perform an impact analysis and define a testing strategy before writing code.
- Code Generation: Implement logic following SOLID, DRY, and KISS principles.
- Atomic Updates: Every task completion requires a git commit and a progress entry.
4. Phase 3: Adversarial Evaluation (The Evaluator)
- Hostile Barrier: Assume the Generator's output is riddled with bugs and happy-path logic.
- Instant Death Gates: Immediately FAIL the task if there is a global regression, linting error, or any lazy code such as placeholders like TODO or FIXME.
- AC Deep-Dive: Confirm every AC has a dedicated test and that test quality metrics like Mock Integrity and Coverage Stability are met.
- Verdict: Return a binary PASS or FAIL. If FAIL, provide a root cause analysis.
5. Phase 4: Remediation and Reconciliation
- Remediation: If the Evaluator returns FAIL, the Generator must suspend new work, reproduce the failure locally, and fix the logic until it passes evaluation.
- Reconciliation: Once PASS is achieved, update the YAML task status to done and log the verification evidence including the git hash and test results in progress.md.
Reference
- Persona - Planner: Focuses on structured YAML roadmap creation and task decomposition.
- Persona - Generator: Focuses on defensive programming, architectural synthesis, and local verification.
- Persona - Evaluator: Acts as the gatekeeper using a Zero-Trust approach to code quality.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: aditikilledar
- Source: aditikilledar/hooligan-harness
- 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.