# Audit Placeholder Code Before Release

Placeholder code hides product risk and can reach production with fake behavior. This skill guides Claude, Codex, or Claude Code through a structured audit that finds, prioritizes, and replaces theater with real implementations.

## Install

```bash
npx skillstore add dnyoussef/theater-detection-audit
```

## Metadata

- Status: approved
- Slug: dnyoussef-theater-detection-audit
- Skillstore revision: r1
- Version status: missing
- Tree hash: 90364da5bef95d8b8f55bea5fe6869505104c20e5239fddffdae9b7b55990968
- Author: DNYoussef
- GitHub username: DNYoussef
- License: MIT
- Repository: https://github.com/DNYoussef/ai-chrome-extension/tree/main/.claude/skills/theater-detection-audit
- Ref: 72d5025b022c77f7a51bdf5c1637c689c80e89d1
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Quality score: 79
- Quality tier: bronze
- Public page: https://skillstore.pages.dev/skills/dnyoussef-theater-detection-audit
- Manifest: https://skillstore.pages.dev/api/skills/dnyoussef-theater-detection-audit/manifest

## Capabilities

- Scans scoped files for TODO, FIXME, HACK, XXX, TEMP, STUB, MOCK, and similar markers.
- Identifies hardcoded responses, mock data, stub functions, commented logic, weak error handling, and test-only paths.
- Reads surrounding context to infer intended production behavior and dependencies.
- Prioritizes findings by operational risk, user impact, and dependency order.
- Produces an audit report with locations, descriptions, completion roadmap, and progress tracking.
- Guides replacement work with validation, logging, security, testing, and documentation checks.

## Use Cases

- Release Readiness Review: Find placeholder logic before a release branch moves to production.
- Legacy Code Handoff: Separate real implementations from mocks when adopting an unfamiliar codebase.
- Prototype Hardening: Convert rapid prototype shortcuts into tracked, prioritized implementation work.

## Prompt Templates

### Find Basic Theater

```
Use the theater-detection-audit skill on the src folder. Find TODO markers, mock data, stub functions, and hardcoded responses. Summarize each item with file, line, risk, and suggested next step.
```

### Prepare A Release Audit

```
Use the theater-detection-audit skill on the release branch. Focus on user-facing flows, API clients, authentication, payments, and error handling. Produce a prioritized completion roadmap.
```

### Map Theater Dependencies

```
Use the theater-detection-audit skill to map dependencies between placeholder implementations. Identify which mocks or stubs block other work, then recommend the safest completion order.
```

### Complete High-Risk Theater

```
Use the theater-detection-audit skill to identify high-risk theater, read full context, design production replacements, and list tests that prove the real behavior works.
```

## Limitations

- Requires a clear audit scope; very large repositories should be reviewed in phases.
- Cannot resolve unclear product requirements without user or stakeholder input.
- May flag legitimate test fixtures unless test and production boundaries are clear.
- Does not replace a dedicated security, performance, or compliance audit.

## Best Practices

- Provide narrow paths, important flows, and release goals before starting the audit.
- Review findings with a domain owner before replacing business logic.
- Add tests that fail against placeholders and pass against real implementations.

## Anti Patterns

- Running the audit across a huge repository without phase boundaries.
- Treating test fixtures as production failures without checking their scope.
- Replacing placeholders before confirming requirements, data sources, and failure behavior.

## Security Audit

- Audited at: 2026-07-06T11:45:37.176\+00:00
- Summary: The three static system-reconnaissance findings are false positives. The skill describes a scoped workflow for finding mock data, stubs, TODO markers, and incomplete code in user-provided projects. No evidence found of prompt injection, secret collection, host reconnaissance, or data exfiltration intent.

## Stats

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