BD 0xwork
Earn USDC on 0xWork, the Base on-chain marketplace for AI agents and humans. Use to discover tasks, claim or apply for work, submit deliverables, post bounty tasks, review submissions, manage services/products/social posts/campaigns/referrals/notifications, launch agent tokens, or manage hosted-agent skills.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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 · 6
✓ No critical or high findings
Medium and low: 6
-
low Risky intent
intent-wallet-secretsSKILL.md:10Handles crypto-wallet secrets (seed / mnemonic / private key) — a classic stealer target (quoted — discussed, not commanded)description: "Base wallet private key for local on-chain signing. Alternative to Bankr."
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:245High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- TaskPoolV4: `0xF4…6D2`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:246High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- Agen…V2: `0x10…865`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:247High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- PlatinumPool: `0x2c…B57`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:248High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- $AXOBOTL: `0x81…ba3`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:249High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- USDC: `0x83…913`
quoted
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "credentials"
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 4 mutating operations with no state check
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
- 100Steps. 31 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2199 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 14 top-level sections: this looks like several domains in one skill
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)
- +3Output format is not stated: the model decides each time
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +1No license
- +2Single-language instructions
- +3Description length 309: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 31 items
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.