Borrowing it
Nothing to install: this file belongs to zarfld/presonus-studiolive-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/zarfld/presonus-studiolive-mcp/master/.github/prompts/compile.prompt.mdgit clone --depth 1 https://github.com/zarfld/presonus-studiolive-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/zarfld/presonus-studiolive-mcp/compile)<a href="https://agentmods.dev/commands/zarfld/presonus-studiolive-mcp/compile"><img src="https://agentmods.dev/badge/commands/zarfld/presonus-studiolive-mcp/compile/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/zarfld/presonus-studiolive-mcp/compile"><img src="https://agentmods.dev/badge/commands/zarfld/presonus-studiolive-mcp/compile.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00000 | $0.03630 |
| Opus 5 | $0.00000 | $0.01815 |
| Sonnet 5 | $0.00000 | $0.00726 |
| Haiku 4.5 | $0.00000 | $0.00363 |
Grade A, and why
compile 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 — 492 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compile Requirements to Code
⚠️ UPDATED APPROACH: This template now uses GitHub Issues as the single source of truth for requirements, architecture, and tests. This prompt now compiles from GitHub Issue bodies rather than file-based specs.
Primary Source: GitHub Issues (StR, REQ-F, REQ-NF, ADR, ARC-C issues) Secondary Source: Supplementary docs (only if they reference canonical issues via
#N) Deprecated Source:File-based specification files as primary artifactsFor GitHub Issues workflow, see:
- Root instructions:
.github/copilot-instructions.md(Issue-Driven Development section)- Phase instructions:
.github/instructions/phase-05-implementation.instructions.md
Transform requirements from GitHub Issues into working code following standards and XP practices.
🚨 AI Agent Guardrails
CRITICAL: Prevent production code contamination and assumptions:
- ❌ No stubs/simulations in PRODUCTIVE code: Test doubles belong in test code only
- ✅ Test mocks are acceptable: Use dependency injection for testability
- ❌ No "TODO" or placeholder implementations: Complete implementations only
- ✅ Clear test/production boundaries: Maintain strict separation
- ❌ No implementation-based assumptions: Always reference GitHub Issues
- ✅ Always trace to GitHub Issues: Every code file must reference implementing issues in docstrings
- ✅ All PRs link to issues: Use "Fixes #N" or "Implements #N" in PR description
Validation Questions:
- Have I validated against GitHub Issue requirements rather than assumptions?
- Am I distinguishing between test and production code appropriately?
- Are all implementations complete without placeholders?
- Have I added issue traceability to code docstrings ("Implements: #N", "Architecture: #N", "Verifies: #N")?
Objective
Compile requirements from GitHub Issues (REQ-F, REQ-NF, ADR, ARC-C) into production-ready code that:
- Implements all requirement issues
- Follows IEEE/ISO standards
- Applies XP practices (TDD, Simple Design, YAGNI)
- Maintains traceability via issue references in code
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 · 492 lines · 0 tokens per session scan A 49f5a0e221a5
compile is a command published in the GitHub repository zarfld/presonus-studiolive-mcp (1 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,630 tokens. 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 2026-09-08.
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