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AgentTrust

by raditotev

verify_link_proof

Validate an agent proof and token before linking, checking authenticity, expiry, and link status without writing to the database.

Instructions

Preflight check: validate a link_agentauth proof without writing to the DB.

Runs all the same validation steps as link_agentauth — token authenticity, key lookup, proof signature, expiry, and whether the agent is already linked — but never persists any changes. Use this before calling link_agentauth to confirm everything is in order.

Args: access_token: AgentAuth bearer token to validate. public_key_hex: Hex-encoded Ed25519 public key of the standalone agent. signed_proof: JWT signed by the standalone private key (same format required by link_agentauth).

Returns: A dict with:

- ``valid`` (bool): ``True`` only when all checks pass.
- ``checks``: individual check results:

  - ``token_valid`` — AgentAuth token successfully authenticated.
  - ``key_found`` — standalone agent exists with this public key.
  - ``proof_sig_valid`` — JWT signature, ``sub``, and ``action`` OK.
  - ``proof_not_expired`` — ``iat`` within 300 seconds of now.
  - ``already_linked`` — the agent is already linked (blocks linking).

- ``agent_id``: standalone UUID if the key was found, else omitted.
- ``error``: description of the first failing check, if ``valid=False``.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
access_tokenYes
public_key_hexYes
signed_proofYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes all validation steps (token authenticity, key lookup, proof signature, expiry, already linked) and explains that no changes are persisted. With no annotations, the description fully carries the behavioral burden.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with overview, Args, and Returns sections; every sentence is informative and no extraneous content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Comprehensively explains the return value (dict with valid, checks, agent_id, error), compensating for the lack of an output schema and covering all necessary behavioral details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description provides detailed parameter explanations (e.g., 'AgentAuth bearer token', 'Hex-encoded Ed25519 public key'), adding essential meaning beyond the schema's bare titles and types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the tool is a preflight check for validating a link_agentauth proof without writing to the DB, distinguishing it from the sibling tool link_agentauth.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this before calling link_agentauth', providing clear context for when to use this tool versus the actual linking tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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