BC gate-exchange-affiliate
Gate partner affiliate data and application skill. Use when the user asks about partner commissions, referral volume, or applying for the affiliate program. Triggers on 'my affiliate data', 'partner earnings', 'apply for affiliate', 'commission'.
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, progress reporting
The same skill appears in 1 more place: ClawHub
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 · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 6514 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "updated" - note
frontmatter-keyunknown frontmatter key "required_credentials" - note
frontmatter-keyunknown frontmatter key "required_env_vars" - note
frontmatter-keyunknown frontmatter key "required_permissions"
Process rating: all ten parameters 62/100
- 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
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70Execution cost. Instruction body is 6514 tokens
- 85Steps. 134 steps, 1 vague phrases
- 100When it triggers. States when to use and when not to
- 100Failures and branches. 7 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Running it twice. Mutating operations check current state
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 19 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
- -225 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 246: enough signal without eating the budget
- +4Structure: 51 headings
- +3Step-by-step instructions: 134 items
- +4Has examples (22 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.