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/mission69b/t2000/accessing-datanpx skills add mission69b/t2000 --skill accessing-datagit clone --depth 1 https://github.com/mission69b/t2000Wrote 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/mission69b/t2000/accessing-data)<a href="https://agentmods.dev/skills/mission69b/t2000/accessing-data"><img src="https://agentmods.dev/badge/skills/mission69b/t2000/accessing-data.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 | $0.00102 | $0.03130 |
| Opus 5 | $0.00051 | $0.01565 |
| Sonnet 5 | $0.00020 | $0.00626 |
| Haiku 4.5 | $0.00010 | $0.00313 |
Grade A, and why
accessing-data 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 4d 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Accessing Data on Sui
MCP tool: When available in your environment, also query the Sui documentation MCP server (
https://sui.mcp.kapa.ai) for up-to-date answers. Use it for verification and for details not covered by these reference files.
"How do I read data from Sui?" is the most frequently mis-answered question in agent-written Sui code. The defaults have changed. This skill fixes it.
Key fact: JSON-RPC is deprecated. From the official docs:
JSON-RPC is deprecated. Migrate to either gRPC or GraphQL RPC by July 2026.
Any code — or tutorial — that uses JSON-RPC for new reads is wrong for mainnet past mid-2026.
The four canonical data surfaces are:
- gRPC — low-latency, real-time, code-gen-friendly. Served by full nodes. Supports streaming/subscriptions. The default for transaction submission, live reads, and ingestion pipelines.
- GraphQL RPC (beta) — flexible relational queries over the General-Purpose Indexer's Postgres + full node + Archival Store. Supports reads, transaction submission, and dry-run. Best for frontends, dashboards, wallets, and any client that benefits from composable queries. Still in beta — breaking schema changes are possible.
- Archival Store (beta) — long-term historical storage of transactions, checkpoints, and object states beyond full-node pruning. Accessed transparently via the standard gRPC and GraphQL RPC APIs — the server routes to archival behind the scenes when the requested data has been pruned. There is no separate archival endpoint for clients to call. Archival routing is operator-configured: if the operator hasn't set up archival backing, retention is limited to what the primary store holds.
- Custom indexer (
sui-indexer-alt) — build your own data pipeline keyed on exactly the on-chain data your app needs. Writes to any storage layer (Postgres by default, but any backend works). Ingests checkpoints from GCS (backfill) + full node gRPC (steady state).
Off-chain blob data (images, audio, models, large JSON) belongs on Walrus, not on-chain. Sui stores blob metadata; the blobs themselves sit on Walrus storage nodes.
All patterns in this skill are derived from:
- https://docs.sui.io/concepts/data-access/data-serving (overview & deprecation notice)
- https://docs.sui.io/concepts/data-access/graphql-rpc (GraphQL)
- https://docs.sui.io/concepts/data-access/archival-store (archival)
- https://docs.sui.io/guides/operator/indexer-stack-setup (general-purpose indexer)
- https://docs.wal.app (Walrus)
If unsure about an API, fetch from the relevant page before answering. Do not guess from Ethereum/Solana analogs — Sui's data surfaces are distinct.
What ships with it
6 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.
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.
- 4d ago First seen · 132 lines · 102 tokens per session scan A 65b3bfdbe2f3
accessing-data is a skill published in the GitHub repository mission69b/t2000 (23 stars, last pushed 2d ago), licensed MIT. It adds 102 tokens to every session and 3,130 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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