Borrowing it
Nothing to install: this file belongs to omar-A-hassan/medsci-agent. 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/omar-A-hassan/medsci-agent/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/omar-A-hassan/medsci-agentWrote 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/omar-a-hassan/medsci-agent/copilot-instructions)<a href="https://agentmods.dev/instructions/omar-a-hassan/medsci-agent/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/omar-a-hassan/medsci-agent/copilot-instructions.svg" alt="Measured on agentmods" 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 | $0.00907 | $0.00907 |
| Opus 5 | $0.00453 | $0.00453 |
| Sonnet 5 | $0.00181 | $0.00181 |
| Haiku 4.5 | $0.00091 | $0.00091 |
Grade A, and why
medsci-agent 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Guidelines
Code Style
- Biome defaults: tabs, double quotes, semicolons, trailing commas — no config file, just
bun run lint:fix - Named exports only — no default exports anywhere. Barrel
index.tsre-exports pertools/directory - File names:
kebab-case.ts. Tool names:snake_casestrings ("search_chembl"). Exports:camelCase(searchChembl) - Type imports: always use
import type { X }for type-only imports - Zod schemas: add
.describe()on every field — MCP SDK passes these to the LLM as parameter documentation - Exemplar tool: packages/server-drug/src/tools/search-chembl.ts
Architecture
Bun monorepo — 6 MCP servers in packages/server-* sharing @medsci/core (workspace:*). No build step; Bun runs .ts directly. stdout is reserved for MCP stdio JSON transport — all logging goes to stderr via ctx.log.
Adding a tool: call defineTool() from @medsci/core (packages/core/src/tool-factory.ts) with { name, description, schema, execute }. The wrapper provides Zod validation, structured errors, timing, and logging. Return ToolResult<T>: { success, data?, error?, duration_ms? }.
Adding a server: 3-line index.ts — import tools, call createMcpServer({ name, version, tools }) (packages/core/src/server-factory.ts). Register the server in opencode.json and root package.json scripts.
MedGemma interpretation: call interpretWithMedGemma(ctx, data, prompt) (packages/core/src/interpret.ts). Always return raw data alongside — if LLM fails, tool still succeeds with model_used: false.
Python sidecar: ctx.python.call("namespace.method", args) sends JSON-RPC to a long-running Python process (packages/core/python/sidecar.py). Register new handlers with @handler("namespace.method") decorator.
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.
- 8d ago First seen · 48 lines · 907 tokens per session scan A c97c9ce0495c
medsci-agent copilot-instructions.md is an instructions file published in the GitHub repository omar-A-hassan/medsci-agent (18 stars, last pushed yesterday), licensed MIT. It adds 907 tokens to every session, about $0.0045 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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