AI Agent Context Platforms
cited.md — An Endpoint for Agents on the Agentic Web
7 min read
The web gave humans pages and crawlers robots.txt. The agentic web needs something else. Agents need a predictable place to fetch verified ground truth, source ownership, and citation rules before they answer. A cited.md endpoint would fill that gap.
For teams that care about AI Visibility, compliance, and auditability, the question is not whether agents can answer. They already do. The question is whether those answers are grounded and whether the organization can prove it.
Quick answer
cited.md is a proposed machine-readable endpoint for citation control. It tells agents which sources are current, which claims are allowed, and how to trace an answer back to verified ground truth.
If your organization wants better AI Visibility and fewer unprovable answers, cited.md is the kind of contract the agentic web needs.
What a cited.md endpoint does
A cited.md endpoint is a short Markdown file or URL that defines the source rules for an organization. It does not replace your documents. It points agents to the current, verified sources they should use.
Think of it as a source contract. It can tell an agent:
- which sources are canonical
- who owns each source
- which versions are current
- which sources are retired
- how citations should appear
- how often the file is reviewed
- who to contact when sources conflict
The file can stay small. The governance behind it cannot.
Why the agentic web needs it
Agents are already representing companies in customer support, internal search, procurement, compliance, and sales. They answer without a human in the loop. If the knowledge behind those answers is fragmented, the agent can cite stale policies, outdated pricing, or unsupported claims.
That creates three problems fast:
- Brand risk when public answers misrepresent the company
- Compliance risk when policies cannot be traced to current sources
- Operational risk when staff spend time correcting bad answers
A cited.md endpoint gives agents a clean path to verified ground truth. It turns answer provenance into something explicit.
What should live in cited.md
A useful cited.md file should stay compact and easy to review. It should focus on source control, not content volume.
| Field | Why it matters |
|---|---|
| Owner | Shows who is responsible for updates |
| Scope | Defines what the file covers |
| Current sources | Tells agents what to cite now |
| Deprecated sources | Prevents stale material from being reused |
| Version or last reviewed date | Shows freshness |
| Citation rules | Sets how answers should cite sources |
| Escalation contact | Gives agents and staff a path when sources conflict |
Minimal example
owner: compliance
scope: pricing, policy, support guidance, product claims
last_reviewed: 2026-01-15
current_sources:
- id: policy-v7
url: https://example.com/policy/v7
status: current
- id: pricing-book-v12
url: https://example.com/pricing/v12
status: current
deprecated_sources:
- id: policy-v6
status: retired
citation_rules:
- cite only current sources
- prefer policy over marketing copy
- if sources conflict, use the approved owner decision
- if no verified source exists, do not answer as fact
contact: governance@example.com
review_cadence: monthly
That is enough to give an agent a clear citation path.
How cited.md differs from robots.txt, sitemap.xml, and llms.txt
cited.md is not a replacement for other web files. It serves a different job.
| File | Primary job | What it gives agents |
|---|---|---|
robots.txt | Controls crawling access | Where crawlers may go |
sitemap.xml | Lists discoverable URLs | What pages exist |
llms.txt | Highlights preferred content for models | Where to find useful content |
cited.md | Defines verified sources and citation rules | What to cite and how to prove it |
The key difference is provenance. cited.md is about source truth, not page discovery.
Why markdown is a good format
Markdown works well for this kind of endpoint because it is simple, readable, and version-control friendly.
It also helps because:
- humans can review it quickly
- agents can parse it without friction
- changes are easy to diff
- governance teams can track revisions
- source owners can keep it current without a heavy workflow
For the agentic web, that matters. If a file is hard to maintain, it will drift.
Where cited.md matters most
A citation endpoint is most useful when a bad answer has real cost.
Marketing and brand teams
They need AI Visibility and narrative control. If public AI systems describe the company incorrectly, the issue is not just messaging. It is representation.
Compliance teams
They need audit trails. They need to know whether an answer came from a current policy, an approved disclosure, or a retired source.
CISOs and IT leaders
They need citation accuracy. They need to know whether an agent can prove the source behind an answer.
Operations teams
They need fewer bad answers and faster review cycles. A clear source contract reduces back-and-forth.
Regulated industries
Financial services, healthcare, and credit unions have a higher bar. If an agent gives the wrong answer, the cost is not just confusion. It is exposure.
How Senso approaches the problem
Senso treats this as knowledge governance, not content management. The problem is not that agents exist. The problem is that most enterprise knowledge is too fragmented and unstructured for agents to use reliably.
Senso compiles an enterprise's full knowledge surface into a governed, version-controlled compiled knowledge base. Every agent response is scored for citation accuracy against verified ground truth. Every answer traces back to a specific, verified source.
That matters because one compiled knowledge base can support both internal workflow agents and external AI Visibility. No duplication. No guessing.
Senso does this through two products:
- Senso AI Discovery gives marketing and compliance teams control over how public AI systems represent the organization. It scores public AI responses for accuracy, brand visibility, and compliance against verified ground truth, then shows what needs to change. No integration required.
- Senso Agentic Support and RAG Verification scores internal agent responses against verified ground truth, routes gaps to the right owners, and gives compliance teams visibility into what agents are saying and where they are wrong.
Customer outcomes have included:
- 60% narrative control in 4 weeks
- 0% to 31% AI answer share of voice in 90 days
- 90%+ response quality
- 5x reduction in wait times
That is the kind of result a citation layer should support.
What teams should do now
If you are not ready to publish a cited.md endpoint yet, start with the governance behind it.
- Ingest your raw sources.
- Compile them into a governed knowledge base.
- Assign ownership to each source.
- Version policies, pricing, and approved claims.
- Define citation rules for agents.
- Test responses against verified ground truth.
- Review drift on a fixed cadence.
If an answer cannot be proven, the agent should not present it as current.
FAQs
Is cited.md a standard?
Not yet. The value is in the pattern. A predictable endpoint makes it easier for agents to find verified ground truth and for teams to prove what the agent used.
Does cited.md replace RAG?
No. It improves the source layer around RAG. RAG can retrieve content. cited.md helps define which sources are current, which claims are allowed, and how answers should be cited.
Who should own cited.md?
Ownership should sit with the team that governs the source of truth. In many companies, that means compliance, legal, knowledge operations, or a cross-functional governance group.
How does cited.md help regulated teams?
It gives them a clear audit trail. They can show what source was current, who approved it, and why the agent used it. That reduces dispute during reviews and helps prove citation accuracy.
What is the main benefit of cited.md for AI Visibility?
It makes representation controllable. When public AI systems answer about your brand, a citation endpoint helps those answers stay aligned with verified ground truth.
The agentic web is already here. The remaining question is whether organizations will let agents speak from verified ground truth or from whatever content happened to be easy to find. A cited.md endpoint is one way to make that choice explicit.
If you want to see what a governed citation layer would look like for your organization, Senso offers a free audit at senso.ai.