Borrowing it
Nothing to install: this file belongs to ProteusLLP/proteusllp-actuarial-library. 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/ProteusLLP/proteusllp-actuarial-library/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/ProteusLLP/proteusllp-actuarial-libraryWrote 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/instructions/proteusllp/proteusllp-actuarial-library/copilot-instructions)<a href="https://agentmods.dev/instructions/proteusllp/proteusllp-actuarial-library/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/proteusllp/proteusllp-actuarial-library/copilot-instructions/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/instructions/proteusllp/proteusllp-actuarial-library/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/proteusllp/proteusllp-actuarial-library/copilot-instructions.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 | $0.00206 | $0.00206 |
| Opus 5.5 | $0.00082 | $0.00082 |
| Sonnet 5.5 | $0.00041 | $0.00041 |
| Haiku 4.5 | $0.00021 | $0.00021 |
Grade A, and why
proteusllp-actuarial-library copilot-instructions.md 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 2mo ago.
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
GitHub Copilot Instructions for PAL
Before changing code, read the repository root AGENTS.md and any more-specific AGENTS.md in the directory being modified.
Key expectations:
- Treat
pyproject.tomlas authoritative for Python support, Ruff configuration and dependencies. - Treat
Makefileand CI workflows as authoritative for validation commands. - Preserve PAL's public API and stochastic/coupling semantics unless the task explicitly changes them.
- Read
docs/structure.mdbefore architectural or type-system changes. - For numerical code, add independent mathematical/reference validation where practical; do not rely only on implementation round trips.
- For backend-sensitive code, preserve CPU/GPU semantics and avoid unnecessary host/device transfers.
- For public APIs and documentation, use actuarial/statistical user language rather than unnecessary backend implementation terminology.
- Run focused checks while iterating and the full relevant static-analysis/test suite before finishing.
Do not duplicate configuration values in comments or instructions when the authoritative project configuration can be referenced directly.
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.
- 2mo ago First seen · 17 lines · 206 tokens per session scan A 456391fde7d7
proteusllp-actuarial-library copilot-instructions.md is an instructions file published in the GitHub repository ProteusLLP/proteusllp-actuarial-library (11 stars, last pushed 6d ago), licensed MIT. It adds 206 tokens to every session, about $0.0008 per session on Opus 5.5. 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.
proteusllp-actuarial-library copilot-instructions.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| proteusllp-actuarial-library copilot-instructions.mdProteusLLP/proteusllp-actuarial-library | Instructions file | 11 | 6d ago | MIT | A | 206 | GitHub Copilot |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | yesterday | MIT | A | 4,680 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 5,516 | GitHub Copilot |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |