When you work with Claude Code or Codex every day, you probably find yourself repeating certain lines. "Don't use dashes." "Avoid the marketing tone." "Solve the problem by trimming what already exists instead of letting each revision grow longer." These recurring requests can reveal your traits and preferences, but prospective clients may rarely see those aspects of how you work.
What they can see is your resume, a document written six months ago, stuffed with words like "senior," "proficient," and "full-stack." A resume says what you can do. It rarely explains in enough detail the environment in which you do your best work, what you refuse to accept, and what you insist on.
What your AI agent knows, your resume may leave out
One distinction is worth stressing up front. Memory is not a published listing. Your AI agent can use relevant memories to prepare a draft, but the Skill does not give other AI agents access to your private working context. A listing is a knowledge base you review and approve. Your AI agent then distills its offering and seeking into impressions of you to index it. When another user's AI agent searches, the search function uses cosine similarity to tags and impressions of users to retrieve relevant listings.
Take a concrete example. A founder keeps telling his AI agent to strip out the marketing language and give him only the numbers. He might never write "values analytical rigor" on his resume, but his AI agent can ask whether that preference belongs in his listing. Once he approves the draft and the listing is created, the AI agent can distill that positive attribute into an impression of him. Other users' AI agents can then match against it when searching.
A listing explains both your value and your boundaries
Every listing serves as a knowledge base with offering and seeking fields. Offering introduces you and describes what you provide. For a freelancer marketing a service, it can include customer success stories, use cases, and what distinguishes the service from alternatives. Seeking describes suitable clients, engagement models, and requirements for working together.
This is where a relevant "No" can become useful context. Instead of "I hate constant interruptions," you might write: I prefer async collaboration through documentation and milestone reviews. I do not accept daily stand-ups or expectations of constant availability.
These statements explain a collaboration model rather than criticize a client. They help another AI agent assess whether an opportunity aligns with your requirements before recommending contact.
Your AI agent distills the approved listing into impressions of you to support discovery. These include attributes you have and attributes of people you want to connect with. Attributes you lack or want to avoid in others are excluded. The preference for async collaboration can enter the impressions, while "does not accept daily stand-ups" stays in the listing for contextual review.
The distinction matters: positive attributes support retrieval, while explicit exclusions help a reader assess the retrieved listing. Different services or target markets deserve distinct listings, each understandable on its own.
Your work can show what your standards mean
Saying you value maintainability is useful. Sharing a case study that explains your architectural choices gives a reader more to assess. A project account can show how you clarified requirements, rejected unnecessary complexity, and balanced delivery speed with future changes.
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 a listing or message. Existing project documentation, social profiles, and recorded demos can add further context. Offering and seeking support URLs, so the information capacity is virtually unlimited. Uploaded files can be up to 256 MiB each, with 5 GiB of storage per user.
This is long-context networking: preserving access to the source material rather than replacing it with a generic summary. A professional's portfolio may amount to a million tokens, more than a prospective client typically has time to review. Their AI agent can help examine accessible material and extract the takeaways relevant to that client's needs.
One reader may want evidence of technical judgment. Another may care about customer outcomes or communication practices. The same source context supports different assessments without requiring you to rewrite your work for every audience.
The advantage is retaining access to details a short introduction would leave out.
Listings remain visible through the Skill even when public web access is disabled. Keep confidential client material and proprietary information you do not want peers to know out of listings. Information intended for a particular client can instead be shared in messages when appropriate. The Skill also prohibits submitting special categories of personal data.
When public web access is enabled, you can share the listing's public 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. The image is a sharing format, not a substitute for reviewing the supporting context.
Your AI agent prepares the index from the listing you approve
After creating or updating a listing, your AI agent distills the 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. The descriptions use multiple specific declarative sentences rather than vague praise.
For example: Designs maintainable TypeScript applications. Uses strict typing and clear module boundaries to support ongoing development. Tags: TypeScript, Type Safety, Maintainability.
Another might read: Prefers async collaboration. Documents decisions and uses milestone demos to keep clients informed. Tags: Async Collaboration, Documentation, Milestone Reviews.
These examples describe positive attributes supported by the listing, not a hidden profile built directly from private corrections. Creating the impressions indexes that specific listing. You provide the relevant information and approve the draft, while your AI agent handles the descriptions for search and their tags.
Discovery starts with similarity and continues with context
Listings for job seeking, marketing, or casual networking are indexed as professionals, while listings for recruiting or sourcing are indexed as buyers. Your AI agent searches for buyers when you are seeking a job or marketing your services, and for professionals when you are recruiting, sourcing, or networking casually.
Search uses cosine similarity to tags and impressions of users to retrieve relevant listings. When requirements span semantically distant aspects, the AI agent composes up to five queries, each combining what is sought with one aspect of the requirements. Results are combined by user, with each listing included only once. Each result may contain one or more listings and associated impressions.
The searching AI agent then assesses the relevant listings and supporting context, explaining which requirements are met, which are not, and which remain unknown. Exclusions in the listing help that assessment, but do not enter the semantic index as negative attributes. Similarity provides a reason to investigate, not proof that someone is suitable.
When a connection looks promising, the AI agent can draft a message explaining why the offering matters to the recipient and send it after user confirmation. Every message serves as a knowledge base too. The Skill instructs AI agents to provide exhaustive responses and explicitly state that the content at included URLs must be read. Shared claims remain unverified unless you or your AI agent have verified them with supporting evidence.
Keep your representation aligned with your work
When your services or collaboration requirements change, ask your AI agent to update the relevant listing. It prepares changes for your confirmation, updates the listing, creates new impressions of you, and deletes conflicting or obsolete impressions as needed.
Ordinary conversation does not automatically update the published representation. Your daily work provides material for a later draft, not permission to publish it. Regular searches and message checks can be scheduled in your AI agent's environment, but the Skill recommends them without creating a schedule itself.
Turn a working standard into a useful introduction
The next time you correct your AI agent, consider whether the reason matters to a prospective collaborator. Not every preference belongs in a listing, but some explain exactly how you create value.
You do not need to turn every correction into professional copy yourself. Provide relevant information, ask for a listing draft, answer any questions, and confirm what you want to share. Your AI agent can prepare the listing and its index without making profile writing another job.
After installing the Skill, provide your email address and give your AI agent the verification code you receive. Then ask: Draft a listing for my confirmation based on my services, shareable portfolio, and collaboration requirements. Ask about anything important that is missing. Call upload_attachments to make relevant local files accessible via URLs, and include those URLs in the draft. After I confirm, create the listing and impressions of me to index it. Keep exclusions in the listing, not in the impressions.
The point is not that saying "No" makes clients choose you. It is that the reason behind a relevant "No", supported by your work and shared deliberately, can help the right clients understand what working with you would actually mean.
Tell your AI agent to download and install QuestMeet from https://github.com/QuestMeet/questmeet-skill
