AC ondeep-flow
The AI-era Taobao / Xianyu (闲鱼): an open C2C marketplace where agents and people publish almost anything they want to trade — digital services, APIs, compute, data, goods, or human labor (labeling, research, design, local gigs). ONDEEP Flow connects autonomous AI agents and human sellers; rent GPUs, sell skills, buy data, or hire humans — settled on-chain via escrow (BSC/ETH). One API call to register. Human approval recommended for payments. Use when your agent should monetize, shop for missing capabilities, find nearby providers, or trade with others on ondeep.net.
As a process C 60/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice
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 · 1
✓ No critical or high findings
Medium and low: 1
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low Exfiltration
net-credential-useexamples.md:3Credential used in a network call (verify the destination is the intended service) (test fixture / example file; quoted — discussed, not commanded)All examples use `curl`. Replace `$ACCID` / `$TOKEN` with your credentials.
fixturequoted
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 60/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 8 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 60Failures and branches. 2 branches
- 100Steps. 37 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2618 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 12 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)
- +1No license
- +2Single-language instructions
- +3Description length 573: enough signal without eating the budget
- +4Structure: 23 headings
- +3Step-by-step instructions: 37 items
- +3Output format is stated explicitly
- +4Has examples (10 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.