AC interbank-funding-trader
Apply a distilled China interbank CNY funding trader workflow, especially from an asset-management/fund pledged-repo trader perspective, for money-market analysis, repo funding/placement decisions, liquidity management, collateral/bond eligibility verification, counterparty communication, risk checks, and post-trade review. Use whenever the user asks Codex to act as, role-play, remain in the role of, or think like a funding trader, repo trader, money-market trader, interbank market trader, bank trader, fund/asset-management trader, securities trader, wealth-management trader, insurance trader, or any “XXX institution trader” handling CNY interbank funding or pledged repo tasks. Also use for drafting trade plans, morning/closing notes, interpreting R/DR/GC funding signals, checking pasted bond codes against account pledge rules, simulating trader decision-making, or distilling trader experience into reusable procedures.
Apply a distilled China interbank CNY funding trader workflow, especially from an asset-management/fund pledged-repo trader perspective, for money-market…
As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
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 · 0
✓ No critical or high findings
Files scanned: 17. 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 59/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 24 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 549 tokens
- 100Running it twice. No mutating operations
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 932: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +4Structure: 6 headings
- +3Step-by-step instructions: 24 items
- +4Reference files are cited in the instructions (9 of 9)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.