BC market-configurable-skills
Call guide and best practices for the configurable crypto price prediction market contracts GouGouBiMarketConfigurable.sol and GouGouBiMarketConfigurableFactory.sol, including factory creation parameters, market configuration fields, core trading/settlement methods, and conventions for calling the contracts from scripts, frontends, or OpenClow workflows via ethers/web3. Use this skill when you need to create new prediction markets, buy YES/NO, swap positions, or redeem settlements.
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 5
✓ No critical or high findings
Medium and low: 5
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:180High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)### 4.2 Price fetching: `getA…pV3`
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:183High-entropy token-like string (may be an id, hash or a credential)function getA…pV3(uint32 startTime, uint32 endTime)
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:199High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- Uses `getA…pV3(priceLookbackSeconds, 0)` to get the settlement-time average price.
quoted -
low Secrets in code
secret-high-entropy-tokenSKILL.md:1046High-entropy token-like string (may be an id, hash or a credential)### 4.2 价格获取：getA…pV3
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:1049High-entropy token-like string (may be an id, hash or a credential)function getA…pV3(uint32 startTime, uint32 endTime)
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 15012 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "language"
Process rating: all ten parameters 53/100
- 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. 28 mutating operations with no state check
- 40Execution cost. Instruction body is 15012 tokens: crowds the task out of the window
- 55Failures and branches. 1 branches
- 100Tools and files. No external tools needed
- 100Steps. 213 steps
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 16 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
- +1No license
- +2Single-language instructions
- +3Description length 486: enough signal without eating the budget
- +4Structure: 48 headings
- +3Step-by-step instructions: 213 items
- +4Has examples (32 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.