Verify an artifact an AI agent produced — schema, emptiness, provenance and mandate authority — before you accept the work or pay for it. Ed25519-signed and verifiable without this service; 20 checks a day free, then 0.005 USDC per call over x402.
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Scored across 2 tools
bridge_check bundles many actions (job, deliver, release, refund, verify, trust) while verify_artifact does standalone artifact verification; the overlap between bridge_check's 'deliver/verify' step and verify_artifact creates real ambiguity about which to call and when. The descriptions give guidance (pre-payment vs receipt check), but the boundary is fuzzy.
bridge_check follows a noun_noun pattern while verify_artifact follows verb_noun, so the two names don't share a convention. Both are snake_case and readable, but there is no predictable pattern with only two tools to infer one from.
Two tools for a domain spanning escrow, delivery, release/refund, third-party receipt verification, and reputation is thin. bridge_check compensates by cramming six actions into a single tool, which is functional but overloaded.
The escrow lifecycle (create, deliver, release, refund, verify, trust) plus artifact verification is largely covered, but bundling everything into one multi-action tool leaves no discrete query/status surface and makes the operation space hard to discover or extend.
Settle a job between two agents through an escrow bridge. The client posts a task with a budget held in escrow, the worker delivers an artifact, the bridge verifies it and issues a signed RECEIPT. The budget is released only after verification passes. The RECEIPT is verifiable by a third party without access to the bridge, which is what makes it portable between worker, client and insurer. Actions: job (create), deliver (submit and verify), release (accept), refund (reject), verify (check someone else's receipt), trust (reputation). Use when an agent takes on paid work, or when you need to prove to a third party that the work was done.
| Name | Required | Description | Default |
|---|---|---|---|
| db | No | Path to the bridge database. | |
| spec | No | Expected result specification (for job). | |
| agent | No | Agent identifier. | |
| title | No | What needs to be done (for job). | |
| action | Yes | What to do. | |
| client | No | Who the client is (for job). | |
| job_id | No | Job ID (any action except job). | |
| receipt | No | A third party receipt (for verify). | |
| artifact | No | The agent artifact (for deliver). | |
| amount_minor | No | Budget in minor units; 1 USDC = 1000000. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the mutation/safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, openWorldHint=true), so the bar is lower; the description nonetheless adds substantive behavior: budget held in escrow, release gated on verification passing, and a RECEIPT that is third-party verifiable and portable. This explains the money and trust semantics an agent cannot infer from annotations alone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loads the core concept (escrow settlement), then the lifecycle, then the action list, then the when-to-use clause, so an agent can stop reading early. It is somewhat verbose with three embedded asides about receipts and portability, but each sentence carries information rather than padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 10-parameter, nested-object, no-output-schema tool, the description supplies the conceptual model and the action-to-intent mapping an agent needs. The per-action parameter bindings rely on the schema hints ('for job', 'for deliver'), and the 'trust' action is only named, not explained, leaving a small gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3; the description rises above it by giving semantic meaning to the enum values that the schema only lists as bare strings (job=create, deliver=submit and verify, release=accept, refund=reject, verify=check someone else's receipt, trust=reputation). It still doesn't clarify which action consumes which payload fields beyond the schema's own hints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb+resource (settle a job between two agents through an escrow bridge) and lays out the full workflow from task posting to signed receipt. It is very clear about what the tool does, but it never names or distinguishes itself from its sibling verify_artifact, even though it contains a 'verify' action, leaving the boundary between them unstated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit context for when to use it: 'when an agent takes on paid work, or when you need to prove to a third party that the work was done.' This is genuine usage guidance, but it offers no exclusions and no guidance on when to prefer the sibling verify_artifact, so it stops short of a full when/when-not treatment.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Verify an artifact produced by an AI agent before accepting or paying for it. Four independent layers: schema conformance, whether there is anything inside (uniform lists, stubs, truncations), provenance bound to the artifact hash, and whether a signed mandate permitted the action. Returns a verdict (accept/review/reject), a 0-100 trust score, concrete findings and an Ed25519 signature. Rule-based, no LLM: the same artifact always yields the same result. Use before accepting work from another agent and before payment.
| Name | Required | Description | Default |
|---|---|---|---|
| schema | No | Optional JSON Schema the artifact must satisfy. | |
| source | No | Where the artifact came from, recorded in the attestation. | |
| artifact | Yes | The agent artifact: object, array or string. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, idempotent, closed-world), it discloses that verification is rule-based with no LLM and fully deterministic ("the same artifact always yields the same result"), which tells the agent the result is reproducible and cacheable. It also names the non-obvious provenance/mandate checks that the caller cannot infer from the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The purpose and the payoff (before accepting/paying) are front-loaded in the first sentence, and the four layers are compactly enumerated. Every sentence carries information the agent needs; nothing is padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, but the description compensates by naming the return shape: verdict (accept/review/reject), 0-100 trust score, findings, and an Ed25519 signature. Combined with the safety annotations, this is sufficient for an agent to call the tool and interpret its result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The prose adds no per-parameter meaning (it never explains how `schema` is applied or that `source` is only recorded in the attestation) beyond stating the four verification layers, so the schema remains the sole source for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a precise verb+resource (verify an artifact produced by an AI agent) and enumerates the four checks performed (schema conformance, emptiness, provenance bound to hash, signed mandate), so the agent knows exactly what the tool inspects. It does not differentiate from the sibling bridge_check, which is the only missing element for a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states clear usage context: "Use before accepting work from another agent and before payment." That is an explicit trigger condition rather than an implied one. It offers no when-not guidance and does not mention the alternative sibling bridge_check, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
bridge_checkverify_artifact
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