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.
git clone --depth 1 https://github.com/ChenZiHong-Gavin/llm-tech-reportWrote 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/rules/chenzihong-gavin/llm-tech-report/llm-tech-report-maintenance)<a href="https://agentmods.dev/rules/chenzihong-gavin/llm-tech-report/llm-tech-report-maintenance"><img src="https://agentmods.dev/badge/rules/chenzihong-gavin/llm-tech-report/llm-tech-report-maintenance/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/rules/chenzihong-gavin/llm-tech-report/llm-tech-report-maintenance"><img src="https://agentmods.dev/badge/rules/chenzihong-gavin/llm-tech-report/llm-tech-report-maintenance.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 | $0.00000 | $0.01077 |
| Opus 5 | $0.00000 | $0.00539 |
| Sonnet 5 | $0.00000 | $0.00215 |
| Haiku 4.5 | $0.00000 | $0.00108 |
Grade A, and why
llm-tech-report-maintenance 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 9d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LLM Tech Report Maintenance
README.md (and its mirror README_CN.md) is the only data file — all reports live there as Markdown tables.
Core rule: links only — never download PDFs, never read/parse PDF content.
README schema
Each company is an ## H2 heading containing one Markdown table:
## Company Name
| Date | Model | Type | Link |
|:-----|:------|:-----|:-----|
| YYYY-MM | Model Name | Type | [Display Text](URL) |
Field definitions
| Field | Format | Example |
|---|---|---|
| Date | YYYY-MM |
2025-01 |
| Model | Official model name / version | DeepSeek-R1 |
| Type | One of the values below | Paper |
| Link | [Display Text](URL) |
[Technical Report](https://arxiv.org/abs/…) |
Allowed Type values
| Type | When to use |
|---|---|
Paper |
Peer-reviewed or arXiv publication |
Technical Report |
Official technical document (not peer-reviewed) |
System Card |
Safety / capability evaluation doc (OpenAI, Anthropic style) |
Model Card |
Model spec / limitations doc (Google, HuggingFace style) |
Blog |
Official company blog post (when no paper exists) |
GitHub |
Official repo (when no paper or blog exists) |
Link priority (highest → lowest)
- arXiv (
arxiv.org/abs/…) — most stable - Official CDN (
cdn.openai.com,assets.anthropic.com,storage.googleapis.com) - Official blog (
openai.com/blog,qwen.ai/blog) - GitHub repo (
github.com/org/repo) - Web Archive (
web.archive.org) — only when the original is dead
If a model has both a paper and a system card, add two separate rows.
Operations
Add a report to an existing company
- Read README.md
- Find the company's H2 section
- Confirm the model is NOT already listed (avoid duplicates)
- Append a new row at the END of that company's table
- Keep chronological order (oldest → newest)
- Mirror the same edit into
README_CN.md, then commit
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.
- 9d ago First seen · 114 lines · 0 tokens per session scan A 16472aacdde6
llm-tech-report-maintenance is a cursor rule published in the GitHub repository ChenZiHong-Gavin/llm-tech-report (37 stars, last pushed 21d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,077 tokens. 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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