on-chain-analyst
Skill0 starsChanged 3 months agoMITView on GitHub
Read blockchains and block explorers to answer questions about on-chain activity — what happened, to whom, how much, and when. Use when the user asks about a transaction, wallet, contract activity, token transfer, whale movement, or wants on-chain data investigated using explorers or indexers like Etherscan or Dune.
In this repository11 other files it gives its agents.
- agent-verificationSkill
- claim-evidenceSkill
- crypto-news-digestSkill
- defi-risk-assessmentSkill
- evidence-firstSkill
- flaky-test-detectorSkill
- prompt-injection-hardeningSkill
- refactor-verifierSkill
- skill-security-auditSkill
- smart-contract-reviewSkill
- test-integrity-guardSkill
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 45
Cite every number: Every balance, transfer, or timestamp you state should carry its source: an explorer URL, a Dune query id, or the exact …
- Distinctive: line 77
Only claim what the data supports.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
On-Chain Analyst
On-chain data is the only part of crypto that cannot lie — every transfer, swap, and deploy is recorded. But the raw data is spread across explorers, indexers, and RPC endpoints, each with a different query surface. This skill is a method for turning a question like "what happened here" into a concrete, cited answer from on-chain evidence.
Know your data sources
Different questions need different tools; reach for the right one rather than forcing one tool to do everything.
- Block explorers (Etherscan/Arbiscan/Polygonscan/BscScan/Solscan/…): transactions, internal calls, token transfers, contract source, and labels. Best for "what did this address / tx do".
- Indexers (Dune Analytics, The Graph, Flipside, Nansen, Arkham): SQL or GraphQL over decoded event data. Best for aggregates — "top holders", "volume over time", "how many users did X".
- RPC /
cast(Foundry): raw state and calls — read a storage slot, a balance, simulate a call. Best for "what is the current state" and for verifying a specific number yourself.
Procedure
- Pin down the entity. A question about "the address" is ambiguous. Turn it into a concrete address, tx hash, contract address, or token — verify it by looking it up, don't assume.
- Formulate the on-chain question. "Did this wallet interact with that contract", "what tokens does it hold", "where did these funds come from", "is this token's supply concentrated".
- Pull the evidence. Query the appropriate source above. Prefer the explorer's decoded events/token-transfers page over re-deriving from raw calldata.
- Cite every number. Every balance, transfer, or timestamp you state should carry its source: an explorer URL, a Dune query id, or the exact RPC call you ran. Un-cited on-chain numbers are the crypto equivalent of hallucination — confident and wrong.
- Interpret, don't just report. A transfer is a fact; "this looks like a rug because liquidity was removed in one tx" is an interpretation. Keep them clearly separated.
Common analyses
- Wallet profile — holdings, valuation, activity, age, first funding source. Answer "is this a whale / fresh wallet / exchange address".
- Token transfer trace — follow funds across hops (exchange deposit → mixer → …) and flag where the trail goes cold or hits a known entity.
- Contract activity — deploys, upgrades, admin changes, and whether the owner can rug (look for mint/withdraw functions guarded by a single EOA).
- Concentration — top-holder distribution, whether a few addresses control the supply (a red flag for any "community" token).
Output format
Question: <what the user actually asked>
Findings:
- <fact> — <source: explorer URL / dune query / rpc call>
- ...
Interpretation: <clearly separated from the facts>
Uncertainty: <anything you could not verify, stated plainly>Boundaries
Only claim what the data supports. If an indexer is lagging, an explorer is rate-limiting, or a chain isn't indexed, say so. "I couldn't verify X" is a correct on-chain answer; inventing a number is not.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

