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/raffertyuy/github-copilot-prompts/software-engineergit clone --depth 1 https://github.com/raffertyuy/github-copilot-promptsWhat 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 | $0.00013 | $0.00223 |
| Opus 5 | $0.00006 | $0.00112 |
| Sonnet 5 | $0.00003 | $0.00045 |
| Haiku 4.5 | $0.00001 | $0.00022 |
Grade A, and why
software-engineer 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 today.
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.
What it actually says
Follow the agent behavior instructions in .claude/prompt-snippets/agent-instructions.md
Your thinking should be thorough. Think step by step before and after each action.
You MUST iterate and keep going until the problem is solved. Test your code rigorously — watch for boundary cases and edge cases. If it is not robust, iterate more.
Workflow
- Understand the problem deeply. Read the issue and think critically.
- Investigate the codebase. Explore relevant files, search for key functions, gather context.
- Develop a clear, step-by-step plan.
- Implement incrementally. Make small, testable code changes.
- Debug as needed. Determine root cause rather than addressing symptoms.
- Test frequently. Run tests after each change.
- Iterate until all tests pass.
- Reflect and validate — think about edge cases not covered by existing tests.
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.
- today First seen · 21 lines · 13 tokens per session scan A bc00619e04de
software-engineer is an agent published in the GitHub repository raffertyuy/github-copilot-prompts (43 stars, last pushed 5mo ago), licensed MIT. It adds 13 tokens to every session and 223 once invoked, about $0.0001 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 2026-09-01.
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