Database
hive-nft-research - Claude MCP Skill
Use this skill when the user asks about NFT collections or assets on EVM chains — ownership, metadata, traits, floor prices, sales, rarity, spam/authenticity checks — like "what's the floor on this collection", "who owns this NFT", "is this collection spam". Use it whenever the user needs current NFT evidence rather than a general explanation of NFTs. For Solana-native assets (mints, DAS, compressed NFTs) use hive-solana-analysis.
SEO Guide: Enhance your AI agent with the hive-nft-research tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to use this skill when the user asks about nft collections or assets on evm chains — ownership, metadat... Download and configure this skill to unlock new capabilities for your AI workflow.
Documentation
SKILL.md# 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
1. Resolve collection contract, token id, wallet, or asset id.
2. Call `search_tools` for metadata, owner, floor, sales, rarity, and spam
capabilities.
3. Call `get_api_endpoint_schema` for each endpoint before calling it.
4. Start with metadata/identity; add floor/sales or owner/rarity only when
relevant.
5. 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."
1. `search_tools` → `{"query": "nft collection metadata floor price sales ethereum", "limit": 5}`
2. `get_api_endpoint_schema` for the metadata, floor, and sales endpoints
returned, then `invoke_api_endpoint` with schema-valid arguments and a
bounded sales window.
3. Report floor (with marketplace scope), recent sales, and freshness using
the template below.
## Report template
```markdown
## Summary
[Collection/token ownership or market read in one or two sentences.]
## Calls made
- Toolset: nft_research
- Endpoint(s): [exact endpoint names]
- Identifiers: [chain, contract, token/asset ids]
## Evidence
- Identity/metadata: [name, supply, verification]
- Market: [floor + marketplace, sales in window]
- Ownership/rarity/spam: [if requested]
- Provenance: [provider, fetched_at, observed_at/cache_age_ms, runtime status per call]
## Caveats
[Marketplace coverage, stale floor, missing metadata, degraded data.]
## Next action
[Trait drilldown, ownership verification, or market comparison — only if needed.]
```
## Gotchas
- NFT metadata can be mutable or stale.
- Spam checks can lag new collections — "not flagged" is not "authentic".
- Floor price is marketplace-scoped unless the provider aggregates.
## Evidence receipt (required)
End every Hive-backed answer with a compact receipt built from the `_hive`
object on each material tool response:
- `provider`, `tool`, `fetched_at`, `observed_at`, `cache_age_ms`, and `runtime_status`
- `receipt_id`, `receipt_version`, server/build version, and SHA-256 input/result
digests when present (self-checks, not signatures)
- `source`, `cache_status`, `truncated`, and any warnings
- canonical chain/entity identifiers plus block, slot, transaction, or query ids
present in provider data
- material provider disagreements and how they were handled
- checks that were unavailable, gated, stale, truncated, or intentionally not run
- a `claims[]` citation from each material statement to exact receipt IDs
- one `coverage[]` entry for every canonical evidence phase, with each gap explained
Never turn missing evidence into a clean result, silently merge conflicting
provider values, or omit a degraded/fallback call from the receipt.
`observed_at` is Hive's first-observation/original cache-population time, and
`cache_age_ms: 0` only means newly retrieved by Hive. Use provider time, block,
slot, transaction, or candle close for source recency; if absent, mark it
unknown. Run `validate_task_result` before presenting the typed workflow result;
it checks structure but cannot authenticate an invented receipt.
## Runtime status handling
If market data is `degraded`, still return the metadata/ownership that
succeeded and label floor or sales metrics as unavailable.
## Hand-offs
- Solana mints, DAS assets, compressed NFTs → `hive-solana-analysis`.
- Wallet-wide NFT exposure → `hive-wallet-investigation`.
- Mint/contract safety before buying → `hive-security-risk`.Signals
Information
- Repository
- hive-intel/hive-crypto-mcp
- Author
- hive-intel
- Last Sync
- 11/3/2026
- Repo Updated
- 10/28/2026
- Created
- 8/18/2026
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