Borrowing it
Nothing to install: this file belongs to nutdnuy/sec-opendata-th. 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/nutdnuy/sec-opendata-th/master/GEMINI.mdgit clone --depth 1 https://github.com/nutdnuy/sec-opendata-thWrote 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/nutdnuy/sec-opendata-th/gemini-md)<a href="https://agentmods.dev/instructions/nutdnuy/sec-opendata-th/gemini-md"><img src="https://agentmods.dev/badge/instructions/nutdnuy/sec-opendata-th/gemini-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/nutdnuy/sec-opendata-th/gemini-md"><img src="https://agentmods.dev/badge/instructions/nutdnuy/sec-opendata-th/gemini-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 | $0.00382 | $0.00382 |
| Opus 5.5 | $0.00153 | $0.00153 |
| Sonnet 5.5 | $0.00076 | $0.00076 |
| Haiku 4.5 | $0.00038 | $0.00038 |
Grade A, and why
sec-opendata-th GEMINI.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 today.
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
Gemini / Antigravity Instructions
Follow AGENTS.md. Treat this repository as the source of truth for SEC Open
Data Thailand access across all AI tools.
Use the Python CLI for data pulls:
.venv/bin/python -m secopendata categories
.venv/bin/python -m secopendata amc-search "กสิกร"
.venv/bin/python -m secopendata fund-search "K-CHANGE" --status Registered
.venv/bin/python -m secopendata request --method GET --path /v1/<category>/<path>
.venv/bin/python -m secopendata request --method GET --path /v2/fund/factsheet/performance --cursor-paginate
.venv/bin/python -m secopendata request --method POST --path /v1/<category>/<path> --json '{"Name":""}'
Use skills/sec-open-api/SKILL.md as the reusable operating guide. Preserve
generic /v1 endpoint coverage for digital assets, funds, Licence Check, One
Report, provident funds, debt, equity, ESG, operators/professionals, investors,
and future SEC portal categories. Use --cursor-paginate for v2 endpoints that
return next_cursor and items.
For /onBording or missing credentials, follow
skills/sec-onboarding/SKILL.md; have the user run the hidden-input setup in
their own terminal. Reuse existing configuration and inspect only redacted
status. For offline lookups, use skills/sec-fund-search/SKILL.md.
Resolve fund and AMC names from the bundled offline catalog before asking for a subscription key. Use the live API when the user needs fresher data or details that are not present in the compact catalog.
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.
- today Changed · +5 lines · +65 tokens per session 96e923431cdf
- 2mo ago First seen · 26 lines · 317 tokens per session scan A dfe001a2be64
sec-opendata-th GEMINI.md is an instructions file published in the GitHub repository nutdnuy/sec-opendata-th (8 stars, last pushed today), licensed MIT. It adds 382 tokens to every session, about $0.0015 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.
sec-opendata-th GEMINI.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| sec-opendata-th GEMINI.mdnutdnuy/sec-opendata-th | Instructions file | 8 | today | MIT | A | 382 | Gemini CLI |
| 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 |