Orkas is a desktop application for commanding a team of AI agents through one chat, with a commander model assigning work to specialist agents in parallel or in sequence. People use it to coordinate research, writing, presentations, and software tasks while keeping files on their computer. The catalogue includes skills for extending the agents available to Orkas.
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.
npx skills add Orkas-AI/Orkas --skill security-researchgit clone --depth 1 https://github.com/Orkas-AI/OrkasWrote 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/skills/orkas-ai/orkas/security-research)<a href="https://agentmods.dev/skills/orkas-ai/orkas/security-research"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/security-research/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/skills/orkas-ai/orkas/security-research"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/security-research.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 | $0.00003 | $0.00538 |
| Opus 5.5 | $0.00001 | $0.00215 |
| Sonnet 5.5 | $0.00001 | $0.00108 |
| Haiku 4.5 | $0.00000 | $0.00054 |
Grade A, and why
security-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 24d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Security Research
Read with market-data for a company thesis, comparison, factor screen, or
watchlist. The goal is a decision-ready evidence map, not a forced rating.
Research contract
- Lock security, listing, market, horizon, currency, and comparison set.
- Prefer filings, exchange notices, and issuer releases for current business facts. Distinguish filing period from retrieval date.
- Separate business quality, growth, balance sheet, cash generation, valuation, price/volume behavior, ownership/liquidity, and event risk.
- Reconcile conflicts rather than averaging them away. Missing a field lowers coverage; it is not neutral or zero.
- End with base/bull/bear cases, catalysts, invalidation conditions, and the next evidence that would change the view.
Run deterministic time-series and supplied-fundamental analysis:
"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" market-data stock -- analyze --input history.json --symbol 600519.SH --source user-file
Run a cross-sectional screen:
"$ORKAS_NODE" "$ORKAS_PC_DIR/bin/run-skill.cjs" market-data stock -- screen --input universe.json
For a requested historical price cutoff, use --cutoff YYYY-MM-DD on analyze
or screen. The core selects bars in memory, preserves the source file and
reports excluded-bar counts. --as-of alone remains strict validation and
rejects later bars. Neither option proves point-in-time availability of
fundamentals or universe membership; keep those evidence gaps explicit.
The screen uses only covered factors, reports eligibility and coverage, and produces a relative research priority—not a buy/sell instruction. Explain each rank through its factor components and name survivorship, point-in-time, FX, and sector-comparability limits when applicable.
For event/news questions, retrieve fresh evidence; do not infer today's event state from historical bars. Rumors remain labeled and never override filings.
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.
- 24d ago First seen · 50 lines · 3 tokens per session scan A 0becdc19a761
security-research is a skill published in the GitHub repository Orkas-AI/Orkas (2,192 stars, last pushed today), licensed MIT. It adds 3 tokens to every session and 538 once invoked, about $0.0000 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 2026-09-23.
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