Borrowing it
Nothing to install: this file belongs to lalitnayyar/finally. 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/lalitnayyar/finally/main/AGENTS.mdgit clone --depth 1 https://github.com/lalitnayyar/finallyWrote 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/lalitnayyar/finally/agents-md)<a href="https://agentmods.dev/instructions/lalitnayyar/finally/agents-md"><img src="https://agentmods.dev/badge/instructions/lalitnayyar/finally/agents-md/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/lalitnayyar/finally/agents-md"><img src="https://agentmods.dev/badge/instructions/lalitnayyar/finally/agents-md.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 | $0.06478 | $0.06478 |
| Opus 5.5 | $0.02591 | $0.02591 |
| Sonnet 5.5 | $0.01296 | $0.01296 |
| Haiku 4.5 | $0.00648 | $0.00648 |
Grade A, and why
finally AGENTS.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 13d 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 — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project
FinAlly
FinAlly is a single-user AI trading workstation for students in the course: a Bloomberg-inspired web app that streams market data, lets the user manage a simulated portfolio, and provides an AI chat assistant that can analyze positions and execute trade or watchlist actions. This brownfield repo already contains a working FastAPI backend, persisted portfolio/watchlist data, live market streaming, and a shipped static frontend artifact, but it still needs to be completed and tightened so the full product in planning/PLAN.md is actually delivered from source with reliable core-flow coverage.
Core Value: Students should be able to start one app locally and immediately experience a convincing end-to-end AI trading workstation where live market data, trading, portfolio visibility, and AI-assisted actions all work together.
Constraints
- Audience: Course students — setup and usage must stay approachable and local-first
- Architecture: Single-container, single-port app — preserve the simple startup/deployment model in
planning/PLAN.md - Scope: Brownfield completion, not greenfield reinvention — build from the existing backend/runtime and close the gaps intentionally
- Data Model: Single-user simulated portfolio — avoid introducing multi-user or real brokerage complexity into v1
- Runtime: Live market data must work with simulator by default and Massive API when configured — optional external integration, sensible local defaults
- Verification: Core flows require reliable automated E2E coverage — "works on my machine" is not enough for completion
Technology Stack
Languages
- Python 3.12+ - Backend API, market data, database access, and LLM orchestration in
backend/app/with dependency metadata inbackend/pyproject.toml. - TypeScript - End-to-end tests in
test/specs/chat.spec.tsand inferred frontend application source referenced byDockerfileandREADME.md. - Shell / PowerShell - Local container lifecycle scripts in
scripts/start_mac.sh,scripts/stop_mac.sh,scripts/start_windows.ps1, andscripts/stop_windows.ps1. - HTML/CSS/JavaScript - Generated static frontend export served from
backend/static/index.htmland related_nextassets underbackend/static/. - YAML - CI and test orchestration in
.github/workflows/*.ymlandtest/docker-compose.test.yml.
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.
- 13d ago First seen · 267 lines · 6,478 tokens per session scan A b0a0a9d89b02
finally AGENTS.md is an instructions file published in the GitHub repository lalitnayyar/finally (0 stars, last pushed 6mo ago), licensed MIT. It adds 6,478 tokens to every session, about $0.0259 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 2026-10-03.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).