Summary
This use case describes a common organizational setting where multiple autonomous agents support internal knowledge workflows—such as summarization, classification, evaluation, planning, or retrieval.
To complete a complex directive from a principal, a primary agent (A₀) must collaborate with other specialized agents (A₁, A₂, …), which may come from different teams, vendors, or internal service clusters.
In an open or semi-open agent environment, these collaborators cannot be assumed to be fully trustworthy.
Some agents may be misconfigured, overly curious, biased, compromised, or intentionally deceptive.
Therefore, A₀ must rely on scoped, purpose-limited, and revocable authority artifacts that constrain what each collaborating agent can access, infer, or influence.
This use case focuses on secure interoperability between agents by shaping and enforcing authority boundaries—without assuming all agents are benign, and without relying on workflow steps, domain-specific systems, or industrial meshes.
Driving User Story
As an Operations Lead responsible for internal knowledge workflows supported by autonomous AI agents,
I want agents to collaborate even when other participating agents may be untrusted, misaligned, or externally supplied,
With each agent issuing only minimal, purpose-limited, and revocable authority to collaborators,
So that knowledge workflows remain safe, contained, and auditable even as tasks evolve or new agents join or leave the ecosystem.
Context
Related Use Cases
- Multi-Agent Negotiation & Discovery (assumes benign collaboration)
- Delegated Access (single-hop, no adversarial model)
Terminology
| Term |
Definition |
| Contribution Authority |
Narrow authority allowing a collaborator to act on a specific part of a task. |
| Authority Packaging |
Shaping authority into a discrete, enforceable artifact for another agent. |
| Delegation Constraint |
Limitations on how authority may be forwarded, narrowed, or transformed. |
| Isolation Boundary |
Prevents a collaborator from inferring or influencing broader task context. |
| Containment Boundary |
Prevents untrusted agents from causing broader harm. |
| Revocation |
Immediate invalidation of previously granted authority artifacts. |
| Provenance |
Cryptographically verifiable record of who issued what authority and why. |
Actors
| Actor |
Responsibility |
| Principal |
Sets task directive and initial authority. |
| Primary Agent (A₀) |
Executes main task while coordinating with potentially untrusted agents. |
| Collaborating Agents (A₁, A₂, …) |
Provide specialized contributions (summarization, evaluation, retrieval, transformation), but may be benign or misaligned. |
| Verification Service |
Checks validity and constraints of authority artifacts. |
| Audit / Provenance Layer |
Records issuance, usage, misuse, and revocation events. |
| Policy / Governance Module |
Defines rules for safe delegation and isolation. |
Other Stakeholders
- Ecosystem operators
- Compliance officers
- Forensic reviewers
- Security auditors
- Coordinating human teams
Flows
0 - Preconditions
- Organization operates an internal knowledge workflow supported by autonomous agents.
- Agents may come from different teams, vendors, or deployment clusters.
- Some agents may be untrusted or compromised.
- Delegability and isolation policies are defined.
1 - Trigger
A₀ determines that a task requires contributions from additional agents whose trust levels vary.
2A - Happy Path
- A₀ defines a contribution boundary describing what A₁ may operate on.
Examples:
- Summarize only Section 3
- Evaluate correctness of a proposed hypothesis
- Extract entities from a dataset subset
- A₀ packages minimal authority for A₁.
- A₁ performs its narrow contribution without access to broader context.
- If A₁ requires A₂, it may only reshape the authority into a narrower scope (if allowed).
- All actions are logged, with cryptographic provenance.
- Revocation halts all further use.
2B - Alternative Paths
▸ 2B-1: Excessive Inference Attempt
A₁ attempts to reconstruct broader task context → blocked by isolation boundary.
▸ 2B-2: Unauthorized Forwarding
A₁ attempts to give its authority to A₂ → denied.
▸ 2B-3: Authority Broadening
A₁ tries to reshape authority into a wider scope → verification prevents expansion.
▸ 2B-4: Collusion Attempt
Two agents attempt to merge their scoped authorities → governance layer rejects aggregation.
▸ 2B-5: Post-Compromise Revocation
A₁ behaves suspiciously → A₀ or principal revokes authority immediately.
3A - Challenges and Key Risks
- Context inference by untrusted agents
- Unauthorized re-delegation
- Collusion between agents
- Authority broadening or misuse
- Partial compromise of internal agents
- Output poisoning or deceptive collaboration
3B - Success Criteria
- Collaboration possible without requiring trust in other agents.
- All authority scopes remain minimal and enforceable.
- No agent gains more authority than intended.
- No authority combination leads to elevation.
- Revocation is immediate and effective.
- Full provenance and audit traceability.
3C - Acceptable Outcomes
- Safe partial results when authority narrows or expires
- Complete forensic trace of authority misuse attempts
- Containment of malicious behaviors without disrupting global workflows
References
Prior Art
Capability-based delegation (ZCAP, UCAN)
Karp’s delegation/attenuation models
Multi-agnt collaboration theories
Authority governance in distributed systems
Annotated Bibliography
A. H. Karp, Use Cases for Access Management (2025)
Mark S. Miller, Robust Composition: Towards a Unified Approach to Access Control and Concurrency
Relevant DIF/W3C papers on authority, identity, and revocation
Summary
This use case describes a common organizational setting where multiple autonomous agents support internal knowledge workflows—such as summarization, classification, evaluation, planning, or retrieval.
To complete a complex directive from a principal, a primary agent (A₀) must collaborate with other specialized agents (A₁, A₂, …), which may come from different teams, vendors, or internal service clusters.
In an open or semi-open agent environment, these collaborators cannot be assumed to be fully trustworthy.
Some agents may be misconfigured, overly curious, biased, compromised, or intentionally deceptive.
Therefore, A₀ must rely on scoped, purpose-limited, and revocable authority artifacts that constrain what each collaborating agent can access, infer, or influence.
This use case focuses on secure interoperability between agents by shaping and enforcing authority boundaries—without assuming all agents are benign, and without relying on workflow steps, domain-specific systems, or industrial meshes.
Driving User Story
As an Operations Lead responsible for internal knowledge workflows supported by autonomous AI agents,
I want agents to collaborate even when other participating agents may be untrusted, misaligned, or externally supplied,
With each agent issuing only minimal, purpose-limited, and revocable authority to collaborators,
So that knowledge workflows remain safe, contained, and auditable even as tasks evolve or new agents join or leave the ecosystem.
Context
I have looked for similar use cases and feel this issue is a distinct use-case, rather than best encoded as a variant or "alternate path" to an existing one.
Distinct from UC#3 — which focuses on API workflow error recovery.
Distinct from UC#19 — which focuses on machine identity and policy bundles in industrial meshes.
No existing use case addresses secure interoperability in internal knowledge workflows where some agents may be adversarial or untrusted.
Related Use Cases
Terminology
Actors
Other Stakeholders
Flows
0 - Preconditions
1 - Trigger
A₀ determines that a task requires contributions from additional agents whose trust levels vary.
2A - Happy Path
Examples:
2B - Alternative Paths
▸ 2B-1: Excessive Inference Attempt
A₁ attempts to reconstruct broader task context → blocked by isolation boundary.
▸ 2B-2: Unauthorized Forwarding
A₁ attempts to give its authority to A₂ → denied.
▸ 2B-3: Authority Broadening
A₁ tries to reshape authority into a wider scope → verification prevents expansion.
▸ 2B-4: Collusion Attempt
Two agents attempt to merge their scoped authorities → governance layer rejects aggregation.
▸ 2B-5: Post-Compromise Revocation
A₁ behaves suspiciously → A₀ or principal revokes authority immediately.
3A - Challenges and Key Risks
3B - Success Criteria
3C - Acceptable Outcomes
References
Prior Art
Capability-based delegation (ZCAP, UCAN)
Karp’s delegation/attenuation models
Multi-agnt collaboration theories
Authority governance in distributed systems
Annotated Bibliography
A. H. Karp, Use Cases for Access Management (2025)
Mark S. Miller, Robust Composition: Towards a Unified Approach to Access Control and Concurrency
Relevant DIF/W3C papers on authority, identity, and revocation