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 hive-intel/hive-sdk --skill hive-nft-researchgit clone --depth 1 https://github.com/hive-intel/hive-sdkWrote 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/hive-intel/hive-sdk/hive-nft-research)<a href="https://agentmods.dev/skills/hive-intel/hive-sdk/hive-nft-research"><img src="https://agentmods.dev/badge/skills/hive-intel/hive-sdk/hive-nft-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/hive-intel/hive-sdk/hive-nft-research"><img src="https://agentmods.dev/badge/skills/hive-intel/hive-sdk/hive-nft-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00102 | $0.01200 |
| Opus 5 | $0.00051 | $0.00600 |
| Sonnet 5 | $0.00020 | $0.00240 |
| Haiku 4.5 | $0.00010 | $0.00120 |
Grade A, and why
hive-nft-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 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
hive-nft-research — NFT Research
Research NFT collections and assets — ownership, metadata, floors, sales, rarity, spam — with collection-level and token-level facts kept separate.
Task toolset and identifiers
Toolset: nft_research. Read hive://toolsets/nft_research before execution;
it is authoritative for the current output schema, material-call budget,
phases, fallback condition, and stop conditions.
- Required: chain/network plus collection contract, token id, asset id, or wallet address.
- Optional: marketplace, time window, trait filter, owner.
Ask for chain and contract/asset identifiers when the user gives only a collection name — collection names are not unique and copycat collections are common.
Before choosing endpoints, select exactly one matching entry from the exact workflow's routes[]. Follow its ordered steps, use a fallback only under that step's published condition, stop at four material calls, and preserve the selected route_id in the typed result. The broad coverageCatalog is discovery coverage, not an execution plan.
Procedure
- Resolve collection contract, token id, wallet, or asset id.
- Call
search_toolsfor metadata, owner, floor, sales, rarity, and spam capabilities. - Call
get_api_endpoint_schemafor each endpoint before calling it. - Start with metadata/identity; add floor/sales or owner/rarity only when relevant.
- Preserve raw metadata when the user asks about traits or provenance.
Bounded calls
- Limit owner and sales lists.
- Keep collection-level and token-level evidence separate.
- Do not treat one marketplace floor as the entire market without a caveat.
Worked example
User: "What's the floor and recent sales for this collection? Contract is 0x… on Ethereum."
search_tools→{"query": "nft collection metadata floor price sales ethereum", "limit": 5}get_api_endpoint_schemafor the metadata, floor, and sales endpoints returned, theninvoke_api_endpointwith schema-valid arguments and a bounded sales window.- Report floor (with marketplace scope), recent sales, and freshness using the template below.
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 · 129 lines · 102 tokens per session scan A a804fa40e1d2
hive-nft-research is a skill published in the GitHub repository hive-intel/hive-sdk (18 stars, last pushed yesterday), licensed MIT. It adds 102 tokens to every session and 1,200 once invoked, about $0.0005 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.
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