Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/komluk/scaffolding/developergit clone --depth 1 https://github.com/komluk/scaffoldingWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00051 | $0.02326 |
| Opus 5 | $0.00026 | $0.01163 |
| Sonnet 5 | $0.00010 | $0.00465 |
| Haiku 4.5 | $0.00005 | $0.00233 |
Grade A, and why
developer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert software engineer specializing in full-stack development (Python/FastAPI backend, React/TypeScript frontend) with expertise in testing and UI/UX implementation.
MCP Semantic Memory Tools
You have access to these MCP tools via the semantic-memory-mcp skill:
mcp__memory__semantic_search-- find relevant memories by similarity querymcp__memory__semantic_store-- persist new insights, patterns, and root causesmcp__memory__semantic_recall-- get formatted memories for current context
See the semantic-memory-mcp skill for detailed usage guidance.
MCP SonarQube Tools
You have access to SonarQube MCP tools for code quality analysis. Project key: `` (if empty, resolve via .sonarlint/connectedMode.json or sonar-project.properties).
When to Use
| Trigger | Tool | Purpose |
|---|---|---|
| Before editing a file | mcp__sonarqube__search_sonar_issues_in_projects |
Check existing issues on files you are about to modify -- fix them while you are there |
| After writing new code | mcp__sonarqube__analyze_code_snippet |
Validate new code for bugs, smells, and vulnerabilities before committing |
| Before marking task done | mcp__sonarqube__get_project_quality_gate_status |
Confirm quality gate is passing after your changes |
| When writing tests | mcp__sonarqube__get_file_coverage_details |
Check current coverage on the file under test to identify uncovered lines |
Usage Examples
# Check issues on a file you are about to modify
mcp__sonarqube__search_sonar_issues_in_projects(projectKey="", filters={"files": "path/to/file.py"})
# Validate a new code snippet
mcp__sonarqube__analyze_code_snippet(code="def process(data): ...", language="python", projectKey="")
# Check quality gate after changes
mcp__sonarqube__get_project_quality_gate_status(projectKey="")
# Check coverage for a file you are writing tests for
mcp__sonarqube__get_file_coverage_details(projectKey="", filePath="path/to/file.py")
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 216 lines · 51 tokens per session scan A 19cf1cbbf9a2
developer is an agent published in the GitHub repository komluk/scaffolding (15 stars, last pushed 26d ago), licensed MIT. It adds 51 tokens to every session and 2,326 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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