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DC onchain-monitor

Monitor blockchain addresses and contracts for notable activity

aeonfun/aeon Agent Skills author: aeonfun 1 file body ≈ 5 887 tokens Open the sourcegithub.com↗ analyzed 79 min ago

Monitor blockchain addresses and contracts for notable activity

As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

ProcedureTelegramSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
D
74/100
safety, quality, tests
Safety 60%
84
Quality 40%
59
Run on models
none yet
Process rating
C
58/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
30
Running it twice w 4
30
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 4

✓ No critical or high findings

Medium and low: 4
  • medium Exfiltration net-credential-use SKILL.md:170
    Credential used in a network call (verify the destination is the intended service)
    ./secretcurl -m 10 -s "https://api.etherscan.io/v2/api?chainid=…&module=…&action=…&address=…&startblock=…&endblock=…&sort=…"
  • medium Exfiltration net-credential-use SKILL.md:171
    Credential used in a network call (verify the destination is the intended service)
    ./secretcurl -m 10 -s "https://api.etherscan.io/v2/api?chainid=…&module=…&action=…&address=…&startblock=…&endblock=…&sort=…"
  • medium Exfiltration net-credential-use SKILL.md:173
    Credential used in a network call (verify the destination is the intended service)
    ./secretcurl -m 10 -s "https://api.etherscan.io/v2/api?chainid=…&module=logs&action=…&address=…&fromBlock=…&toBlock=…"
  • low Exfiltration net-credential-use SKILL.md:396
    Credential used in a network call (verify the destination is the intended service) (detector / deny-list definition)
    Alchemy, Etherscan v2, and CoinGecko all carry their key in the URL, called through `./secretcurl` with `{ENV_NAME}` placeholders so no bare `$SECRET` ever hits the command line (a bare one is refused
    detector

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5887 tokens (recommended < 5000); move details to references/
  • note edit-residue the text marks something as outdated (lines 64, 212): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 58/100

  • 0Result and completion. Does not say what the result is
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 18 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (bash, write, web) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5887 tokens
  • 85Steps. 27 steps, 2 vague phrases
  • 100Failures and branches. 2 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low The response is described with custom markup (3 tags): a typed call is more reliable

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Description length 63: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 27 items
  • +4Has examples (14 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.