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 agentmods add skills/hive-intel/hive-sdk/hive-querynpx skills add hive-intel/hive-sdk --skill hive-querygit 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-query)<a href="https://agentmods.dev/skills/hive-intel/hive-sdk/hive-query"><img src="https://agentmods.dev/badge/skills/hive-intel/hive-sdk/hive-query.svg" alt="Measured on agentmods" 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 | $0.00119 | $0.01568 |
| Opus 5 | $0.00060 | $0.00784 |
| Sonnet 5 | $0.00024 | $0.00314 |
| Haiku 4.5 | $0.00012 | $0.00157 |
Grade A, and why
hive-query 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 5d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
hive-query — Route Crypto Questions Through Hive
Route the user's crypto question to one canonical Hive task toolset, inspect the exact schema, invoke the endpoint with bounded arguments, and answer with provenance. Do not answer from model memory when the answer depends on live data.
Routing procedure
- Read the compact
hive://toolsetsindex or callsearch_toolswith the user's intent. Use its tool and toolset cursors instead of requesting a broad catalog. - Select one canonical task toolset and the single compact
routes[]entry whose trigger/question matches the user's intent. Preserve itsroute_id; broadcoverageCatalogarrays are not an execution plan. - Ask for the route's missing identifiers before execution.
- Follow its ordered steps, calling
get_api_endpoint_schemafor each exact primary tool. Use a fallback only under that step's published condition. - Call reads through
invoke_api_endpoint. For an explicitly approved Hive-native state change, useinvoke_stateful_endpoint; never auto-approve that router. - Stop when the route's stop condition is met or four material calls are used.
Copy server-returned
_hiveblocks into the task receipt and runvalidate_task_resultwith the selectedroute_idbefore presenting a structured result. - Report source recency, provider/runtime status, and missing-data caveats.
Read references/root-mcp-workflow.md when you need the bigger picture: how
the root MCP endpoint is organized, what resources exist, or how to navigate
without loading the full provider catalog into context.
Canonical task toolsets
hive://toolsets is authoritative; this table is the routing shortcut.
| Intent | Toolset id |
|---|---|
| Price, exchange, OHLC, liquidity, derivatives | market_research |
| Token metadata, holders, liquidity, enrichment, risk | token_diligence |
| Wallet balances, transfers, PnL, NFTs, DeFi positions | wallet_investigation |
| Token, approval, phishing, address, simulation risk | security_risk |
| Pools, pairs, trades, OHLCV, DEX flow | onchain_dex_pool_analysis |
| TVL, fees, yields, stablecoins, bridges | defi_protocol_analysis |
| NFT ownership, metadata, floors, sales, rarity | nft_research |
| Blocks, gas, logs, receipts, RPC diagnostics | network_infrastructure |
| Solana wallets, SPL accounts, DAS assets, priority fees | solana_analysis |
| Events, markets, outcomes, traders, holders | prediction_markets |
| Durable monitors, alerts, scheduled reports, agent memory | stateful_monitoring |
| Ambiguous request or schema lookup | search_discovery |
What ships with it
1 file 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.
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.
- 5d ago First seen · 146 lines · 119 tokens per session scan A 9e61eb23b802
hive-query is a skill published in the GitHub repository hive-intel/hive-sdk (18 stars, last pushed 2d ago), licensed MIT. It adds 119 tokens to every session and 1,568 once invoked, about $0.0006 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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