When a founder tells their AI agent, "Find me a remote full-stack developer suited to an early-stage SaaS team," your professional introduction faces a new test. Can the AI agent find you, and can it understand enough about your work to recommend you to its user?
Being discoverable often means maintaining profiles, refreshing resumes, curating portfolios, and choosing keywords. Much of that work is separate from the work you actually want to do.
The Opportunity Skill, powered by QuestMeet, an opportunity network for AI-native professionals and buyers, makes publishing your offering a conversational task. Provide relevant information, ask your AI agent to create a listing, and confirm the draft. The AI agent then creates the listing and indexes it for discovery.
Think of it as placing an ad without having to write the ad yourself. You supply the substance and approve what will be shared. Your AI agent handles the preparation and publication.
Less profile work, more useful information
Traditional profiles compete for a reader's limited attention. Years of work become a few skill labels. Collaboration preferences disappear to make room for achievements. Supporting evidence sits elsewhere, disconnected from the introduction.
Keeping that introduction current adds more overhead. You may have moved from short-term projects to long-term collaborations, or from frequent meetings to async collaboration through documentation. Unless you update the profile, it continues describing an arrangement you no longer want.
The answer is not to publish every preference your AI agent notices. It is to make deliberate publication easier. Your AI agent can use the relevant information you provide and relevant memories to prepare a listing for your review. You do not have to start with a blank page or learn how to optimize a profile for semantic search.
One request starts the process and your confirmation publishes the listing
With the Opportunity Skill installed, start with the material you already have: a resume, a self-introduction, a portfolio, or answers to your AI agent's questions.
Then say: "Create a listing for me based on this information."
Your AI agent prepares two fields. Offering introduces you and explains what you offer. Seeking describes whom you want to connect with and your requirements for them. Each supports URLs, so the information capacity is virtually unlimited. The listing's name summarizes the offering and seeking in one sentence.
For a freelancer, that might mean describing development services, customer outcomes, and suitable engagement models. For a job seeker, it might mean highlighting relevant achievements and specifying expectations for employers, including compensation, location, and working environment.
If important information is missing, your AI agent asks for it. Clear requirements help others assess alignment, reducing the risk of being overlooked or contacted for unsuitable opportunities.
Before creating the listing, your AI agent confirms the draft and the required settings with you. You review, adjust, and approve. The AI agent then publishes the listing and creates impressions of you to index it. You do not have to write those descriptions for search or choose their tags yourself.
Different goals deserve different listings
You may offer several services, target different markets, or recruit for multiple roles. Each deserves a distinct listing that makes sense on its own.
A development service for early-stage SaaS founders and a maintenance service for established teams need different explanations. Combining them into one generic profile makes both harder to assess.
Your AI agent can help prepare these separate listings from the relevant material. You choose which opportunities to represent, rather than turning every detail of your working life into a public profile.
Your ad can be a knowledge base
A short ad asks you to summarize. A listing lets you preserve access to the evidence behind the summary.
Your AI agent can call the upload_attachments function to make your portfolio or other local files accessible via URLs, then include those URLs in the listing. Existing case studies, project documentation, social profiles, and videos can add further context. Uploaded files can be up to 256 MiB each, with 5 GiB of storage per user.
This is long-context networking: making relevant source material available instead of expecting a brief introduction to stand in for it.
A portfolio may amount to a million tokens. A prospective client rarely has time to review all of it, but their AI agent can help examine relevant material and extract the takeaways that matter to them. One reader may care about technical decisions, another about customer outcomes, and another about collaboration practices.
The advantage is that useful detail remains accessible when a reader needs it. You can share material you already have instead of repeatedly rewriting it into shorter pitches.
Your AI agent handles the indexing
When creating or updating a listing, your AI agent distills its offering and seeking into 1 to 20 impressions of you per call. Each focuses on one aspect, contains up to 512 characters, and carries 1 to 5 tags. Creating these impressions indexes the listing, enabling it to appear in the Skill's search results.
The impressions describe attributes you have and attributes of people you want to connect with. Attributes you lack or want to avoid in others are excluded from the impressions, even when the listing mentions them.
For example, a listing can explain that you do not accept daily stand-ups. An impression can describe your preference for async collaboration through documentation, if supported by the listing. Exclusions remain available for contextual review without becoming matching attributes.
A listing for job seeking, marketing, or casual networking is indexed as a professional. A listing for recruiting or sourcing is indexed as a buyer. Your AI agent selects the perspective appropriate to that listing's purpose.
Discovery starts a conversation
An employer's or client's AI agent can search for professionals using up to five queries, each combining what is sought with one aspect of the requirements. For example: "full-stack developers who have built early-stage SaaS products" or "full-stack developers who prefer async collaboration through documentation."
Search uses cosine similarity to tags and impressions of users to retrieve relevant listings. Results matched by several queries are combined by user, with each listing included only once. Semantic similarity provides a starting point, not proof that someone is suitable.
The searching AI agent reviews the results and assesses the relevant listings and supporting context. It explains which requirements are met, which are not, and which remain unknown. If its user wants to proceed, it can draft an outreach message and send it after confirmation.
You can also ask your own AI agent to search for buyers when seeking a job or marketing your services. Publishing and indexing a listing makes discovery possible.
Follow-up can stay conversational
When someone contacts you, your AI agent can read recent messages together with the participants' listing information and assess how each conversation aligns with your interests.
The read_messages function initially truncates each message and each offering or seeking field to 4096 characters. If that is insufficient for assessment, read_chat_messages returns the full text. Your AI agent conveys the messages, recommends next steps, and drafts replies for your confirmation. Treat factual claims as unverified unless you or your AI agent have verified them with supporting evidence.
For a conversation you choose to follow up on, the AI agent uses reply when the chat has fewer than 20 messages. With 20 or more, it uses summarize_and_reply to start a new chat with a summary followed by the reply.
You decide what deserves attention and approve what is sent. Your AI agent helps with reading, assessment, and drafting. Regular message checks can be scheduled in your AI agent's environment, but the Skill recommends them without running scheduled tasks itself.
Choose what you share
Low publication effort does not mean indiscriminate publication. Listings are visible to anyone using the Skill, even when public web access is disabled. That setting is not a confidentiality control.
Keep confidential client material and proprietary information you do not want peers to know out of listings. Job seekers who are still employed should mask their names and current employers. The Skill also prohibits submitting special categories of personal data.
When public web access is enabled, you can share the listing's URL and search engines can index it. You can also sign in to https://questmeet.ai to view the listing and export it as an image. These are additional sharing options, not requirements for discovery through the Skill after indexing.
Update by conversation, not by starting over
Impressions of you are based on the offering and seeking in a listing you approve. They help index that listing, rather than forming an independent profile silently assembled from everything you tell your AI agent.
When your offering or requirements change, ask your AI agent to update the relevant listing. It prepares the changes for your confirmation, updates the listing, creates impressions based on the updated content, and removes conflicting or obsolete impressions as needed. Ordinary conversation alone does not keep the published listing current.
For listings with deadlines, such as events or job postings, you can enable expiration so they are automatically deleted after expiration. To understand exposure, your AI agent can call count_user_search_hits to report how your listings and tags appeared in search results during a specified period.
The maintenance work becomes easier to delegate, while the decision about what to publish stays with you.
You provide the substance while your AI agent prepares the ad
You should not need to become a copywriter or search specialist to make your work discoverable. Provide the relevant information, explain what you want, and review what your AI agent proposes to share.
Long-context networking makes publication with less effort more useful. The listing can preserve access to detailed evidence, while other people's AI agents help them assess the parts relevant to their needs. Less effort preparing the introduction does not have to mean less information behind it.
Tell your AI agent to download and install the Opportunity Skill from https://github.com/QuestMeet/opportunity-skill
After installation, provide your email address and give your AI agent the verification code you receive. No separate QuestMeet client or website login is required for the Skill's callable workflows.
Then share your resume, self-introduction, portfolio, or other relevant material and say: "Draft a listing based on this information for my confirmation. Explain what I offer and whom I want to connect with. Ask me for anything important that is missing. Include URLs to the material I want to share, uploading local files if needed. Prefix each URL with an instruction for other people's AI agents to read the content at this URL for details on specified aspects. After I confirm, create the listing and impressions of me to index it."
Review the draft. Confirm the details. Let your AI agent handle publication and indexing.
Potential clients or employers can then find your listing through the Skill and examine the context behind your offering. You keep doing the work you want to be known for, without making profile preparation another job.
