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 ShurikenTrade/shuriken-skills --skill learn-about-shurikengit clone --depth 1 https://github.com/ShurikenTrade/shuriken-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/shurikentrade/shuriken-skills/learn-about-shuriken)<a href="https://agentmods.dev/skills/shurikentrade/shuriken-skills/learn-about-shuriken"><img src="https://agentmods.dev/badge/skills/shurikentrade/shuriken-skills/learn-about-shuriken/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/shurikentrade/shuriken-skills/learn-about-shuriken"><img src="https://agentmods.dev/badge/skills/shurikentrade/shuriken-skills/learn-about-shuriken.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 | $0.00058 | $0.00408 |
| Opus 5 | $0.00029 | $0.00204 |
| Sonnet 5 | $0.00012 | $0.00082 |
| Haiku 4.5 | $0.00006 | $0.00041 |
Grade A, and why
learn-about-shuriken 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 12d 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
Learning about Shuriken
This skill is a thin pointer. The Shuriken feature surface evolves quickly — do not answer from cached knowledge about what features exist, how they work, or what's supported.
Approach
- Fetch the current platform docs index first. Call
fetch_shuriken_docs(defaults tollms.txt). That index lists every concept, feature area, REST endpoint group, SDK, and guide available right now. - Follow the links that match the user's question. If the index references a specific page, fetch that page with
fetch_shuriken_docsand apathargument. - Only answer from content you just fetched. Cached beliefs about feature X existing, or feature Y working a certain way, are unreliable and may be outdated.
When this skill is the wrong choice
- User is writing code or asking about endpoints, request shapes, SDK usage → use
shuriken:api-integrationinstead. - User is asking about agent key creation / scope selection → use
shuriken:agent-keysorshuriken:scoping.
Pointers
- Platform documentation index:
fetch_shuriken_docs(defaults tollms.txt) — lists concepts, features, REST API, SDKs, guides. - Expanded single-document dump:
fetch_shuriken_docswithpath: "llms-full.txt"— only when the index doesn't point at a specific page and you need everything inline. - Related skills:
shuriken:api-integration,shuriken:agent-keys,shuriken:scoping.
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.
- 12d ago First seen · 26 lines · 58 tokens per session scan A 9918cb1e3a7d
learn-about-shuriken is a skill published in the GitHub repository ShurikenTrade/shuriken-skills (90 stars, last pushed 4mo ago), licensed MIT. It adds 58 tokens to every session and 408 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
Other skills, from other repositories
coinversaa-pulse
Read-only crypto intelligence for AI agents. 103 tools (OAuth 2.1 on the hosted endpoint, API key for local stdio) for Hyperliquid trader analytics, builder-fee revenue analytics, position lifecycles with MAE/MFE execution quality, trader archetype discovery, behavioral cohorts, HIP-4 outcome contracts, outcome/perp…
crypto-report
Analyze cryptocurrency projects with tokenomics, on-chain metrics, and market analysis. Generate comprehensive crypto research reports.
crypto-analyze
Full Crypto Analysis Orchestrator — launches 5 parallel subagents for comprehensive multi-dimensional token analysis with composite Crypto Score.
crypto-onchain
On-Chain Analytics Agent — whale movements, exchange flows, active addresses, network growth, holder distribution, and transaction metrics with On-Chain Score (0-100).
emblem-memecoin-scout
Memecoin discovery and risk assessment via EmblemAI. Trending memecoins on Solana, Base, and Hedera. Pump.fun and LaunchLab new token alerts, Clanker discovery, rug-pull detection, holder analysis, and smart money tracking. Use when the user wants to find new memecoins, check if a token is a rug pull, or scout…
emblem-defi-yield
DeFi yield research and liquid staking via EmblemAI. Discover yield opportunities, compare protocols, check DeFi positions with Nansen, and enter liquid staking via token swaps. Use when the user wants to research yields, find staking options, or review DeFi positions.