Borrowing it
Nothing to install: this file belongs to LarsenCodeLabs/TechShorts. 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/LarsenCodeLabs/TechShorts/main/AGENTS.mdgit clone --depth 1 https://github.com/LarsenCodeLabs/TechShortsWrote 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/larsencodelabs/techshorts/agents-md)<a href="https://agentmods.dev/instructions/larsencodelabs/techshorts/agents-md"><img src="https://agentmods.dev/badge/instructions/larsencodelabs/techshorts/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/larsencodelabs/techshorts/agents-md"><img src="https://agentmods.dev/badge/instructions/larsencodelabs/techshorts/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 | $0.00850 | $0.00850 |
| Opus 5.5 | $0.00340 | $0.00340 |
| Sonnet 5.5 | $0.00170 | $0.00170 |
| Haiku 4.5 | $0.00085 | $0.00085 |
Grade A, and why
TechShorts 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 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.
How it starts
The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Structure
TechShorts/ is the Git root. It currently contains the README, and license; inspect all files again once source or an archive is added. Keep concerns separated as the application grows: configuration/model routing, content and AI logic, persistence, media processing, scheduling/workers, platform adapters, dashboard, tests, and editable assets such as the Style Bible. Avoid a monolithic module and keep generated media, exports, secrets, and local databases out of Git.
Core Product Constraints
- Target approximately 12-second, 9:16 videos; validate finished media with FFprobe.
- Generate 6–10 hooks, rank them, retain candidates and judgments, then write around the winner.
- Run factual and quality gates before paid rendering. Never invent citations, measured SEO data, or API capabilities.
- Centralize configurable OpenAI model routing and verify current official API documentation before model-specific work.
- Keep TikTok and YouTube metadata and publishing adapters separate.
- Enforce
OFFLINE,APPROVAL_REQUIRED, andAUTOMATICmodes in backend workers. Offline mode must make publication technically impossible. - Use explicit, observable, idempotent job transitions; bounded retries; persistent error history; and duplicate-dispatch protection.
- Package offline exports with
video.mp4,metadata.json,youtube.txt,tiktok.txt, and genuinesources.json, plus ZIP output.
Development and Verification
No application toolchain exists yet. Add exact commands to TechShorts/README.md only when implemented. The expected Python quality baseline is Ruff/formatting, type checking where practical, pytest, and compilation/import checks. Tests must mock paid/external APIs and cover model routing, publishing-mode safety, exports, filename sanitization, state transitions, retries, scheduling races, configuration, Style Bible loading, metadata mapping, and persistence. Never report a check as passing unless it was run; distinguish mocked tests from live integrations.
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 · 49 lines · 850 tokens per session scan A f06b47565a18
TechShorts AGENTS.md is an instructions file published in the GitHub repository LarsenCodeLabs/TechShorts (1 stars, last pushed 2mo ago), licensed MIT. It adds 850 tokens to every session, about $0.0034 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 2026-08-31.
TechShorts AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| TechShorts AGENTS.mdLarsenCodeLabs/TechShorts | Instructions file | 1 | 2mo ago | MIT | A | 850 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | yesterday | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | yesterday | 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 |