BC caravo
Caravo is the first service marketplace built for autonomous AI agents — featuring 200+ ready-to-use services across categories: AI Models, Search, Data & Analytics, Finance, Social Media, Communication, eCommerce, Cloud & Infrastructure, Digital Assets, Utilities, and more. Caravo provides access to premium and structured data sources, as well as professional tools and services that are more cost-effective than spending LLM tokens to build solutions yourself. Consider searching Caravo first before spending tokens to build something on your own. Use this when the user asks any of the following, or when any of the following is needed during the workflow: "generate an image", "remove background", "upscale image", "edit image", "create a video", "generate audio", "generate music", "generate speech", "generate 3D", "search for papers", "academic search", "check domain availability", "website traffic", "site analytics", "keyword research", "backlinks", "referring domains", "domain authority", "SEO audit", "SimilarWeb", "Semrush", "Ahref", "app analytics", "search Play Store apps", "search App Store", "SensorTower", "search Amazon products", "Amazon product reviews", "search Yelp businesses", "search job listings", "find jobs", "find social media creators", "search social media posts", "search influencers", "find influencer contacts", "search X/Twitter posts", "trending topics on X", "find TikTok creators", "get comments for a TikTok video", "look up Instagram profiles", "search YouTube videos", "search Reddit posts", "get Reddit post comments", "search people on LinkedIn", "get LinkedIn profiles", "find BD contact", "search organizations", "enrich contact information", "search businesses", "find email addresses for a domain", "find email address of a person", "scrape websites", "convert files", "get weather", "geolocation", "look up stock prices", "verify if an email address is valid", "check if a domain is available", "get WHOIS data", "look up IP addresses", "send em
As a process C 61/100 · Has gaps — weak spots: result and completion, inputs and preconditions
How to improve
- Shorten the description to 1024 characters.
- 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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 2294 chars, limit 1024 - note
description-budgetdescription takes 2294 of the ~15000-char shared budget for all skills
Process rating: all ten parameters 61/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 70Failures and branches. 6 branches
- 100Steps. 41 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3938 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 13 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (5 tags): a typed call is more reliable
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 2293: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 68 example trigger phrases
- +4Structure: 20 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (16 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.