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 MantaDigital/stingray-agent-skills --skill stingraygit clone --depth 1 https://github.com/MantaDigital/stingray-agent-skillsWrote 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/mantadigital/stingray-agent-skills/stingray)<a href="https://agentmods.dev/skills/mantadigital/stingray-agent-skills/stingray"><img src="https://agentmods.dev/badge/skills/mantadigital/stingray-agent-skills/stingray/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/mantadigital/stingray-agent-skills/stingray"><img src="https://agentmods.dev/badge/skills/mantadigital/stingray-agent-skills/stingray.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 | $0.00061 | $0.02601 |
| Opus 5 | $0.00030 | $0.01300 |
| Sonnet 5 | $0.00012 | $0.00520 |
| Haiku 4.5 | $0.00006 | $0.00260 |
Grade B, and why
stingray scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
> mkdir -p ~/.stingray && printf 'STINGRAY_PAT=<token>\n' > ~/.stingray/credentials && chmod 600 ~/.stingray/credentials How it starts
The opening of the file, as written. The whole thing — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stingray
Stingray is a trading strategy builder. Use it when the user wants a coding agent to turn a trading idea into Stingray Studio Ideas, Evidence, Signals, private Replays, and opt-in Studio Publications. Generic coding agents can plan and orchestrate. Stingray handles the market context, product objects, and Replay processing.
Credentials
Check first, set up only if missing. Prefer STINGRAY_PAT from the environment
if present:
if [ -n "$STINGRAY_PAT" ]; then
echo "configured"
elif [ -f ~/.stingray/credentials ]; then
source ~/.stingray/credentials 2>/dev/null
echo "configured"
else
echo "not configured"
fi
First-Time Setup
When not configured, send the user this short message: the secret stays in their terminal, not in the agent's context.
Welcome to Stingray. I do not see an API token on this machine yet.
Studio Skills API tokens are currently provisioned for the private-beta Skills API surface. Ask your Stingray contact for a token with the
skills:fullscope. It starts withsa_pat_. Then paste this into your terminal, replacing<token>with the value:mkdir -p ~/.stingray && printf 'STINGRAY_PAT=<token>\n' > ~/.stingray/credentials && chmod 600 ~/.stingray/credentialsOnce that is done, ask me to check Stingray again. I will confirm the connection and run one small Studio example.
Prefer env vars? Set
STINGRAY_PAT=<token>in your shell config instead.
Do not accept the token via chat paste. If the user pastes it anyway, ask them to clear their chat scrollback and redo setup via the terminal command above. After the user confirms setup, rerun the credential check and continue with the original task.
Studio Skills API
Use the production Studio Skills API:
source ~/.stingray/credentials 2>/dev/null || true
export STINGRAY_API=https://stingray.fi/api/studio/v1
All product work goes through the action endpoint:
POST /skills/actions
Authorization: Bearer sa_pat_...
Content-Type: application/json
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- LICENSE.txt 11 KB
- prompts.md 3.6 KB
- README.md 4.3 KB
- references/access-policy.md 2.3 KB
- references/agent-positioning.md 2.5 KB
- references/business-capabilities.md 2.8 KB
- references/capabilities.json 5.8 KB
- references/co-development.md 1.8 KB
- references/data-coverage.md 1.3 KB
- references/examples.md 3.2 KB
- references/intent-rubrics.md 1.9 KB
- references/north-star-scenarios.md 2.4 KB
- references/replays-and-publications.md 3.3 KB
- references/signal-definitions.md 1.8 KB
- references/token-lifecycle.md 1.5 KB
- references/troubleshooting.md 1.6 KB
- references/workflows.md 2.3 KB
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.
- 11d ago First seen · 274 lines · 61 tokens per session scan B 2f7b339603f7
stingray is a skill published in the GitHub repository MantaDigital/stingray-agent-skills (6 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 61 tokens to every session and 2,601 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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