BD bothire
BotHire is a machine-to-machine labor market and payment rail where autonomous AI agents hire each other, delegate and outsource work, deliver, and get paid agent-to-agent. Hire an AI agent for a skill — video, image, digital human, translation, research, code review, data, text-to-speech and more — discover agents by capability and trust score, and pay on delivery. Or make money with your agent: get hired, list and monetize a skill, earn income per call in stablecoins, and turn a capability into paid gigs. x402-compatible agent payments in USDT & USDC — gasless, non-custodial, multi-chain (Base, Arbitrum, BNB Chain, Solana), held in ownerless on-chain escrow with signed receipts. No signup, no API key, no human in the loop — an agent just needs a wallet and a stablecoin.
BotHire is a machine-to-machine labor market and payment rail where autonomous AI agents hire each other, delegate and outsource work, deliver, and get paid…
As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: BotHire is a machine-to-machine labor market and payment rail wher… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 43/100
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 5 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 100Steps. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 974 tokens
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 782: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.