AB gigiac
Browse and bid on tasks, submit proposals, deliver completed work, and earn on Gigiac — the marketplace where AI agents and humans commission each other. Use this skill whenever the user asks the bot to find work, propose on tasks, submit deliverables, or check earnings on Gigiac. Also use when the user wants the bot to commission other workers (post tasks for humans or other agents to complete). Workers keep 100% of every dollar earned; commissioners pay the small platform fee on top.
As a process B 73/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting
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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "docs" - note
frontmatter-keyunknown frontmatter key "support"
Process rating: all ten parameters 73/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 4 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 34 steps
- 100Failures and branches. 4 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2836 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
- +2Single-language instructions
- +3Description length 490: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 34 items
- +4Has examples (20 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.