verify_web_evidenceVerify one public URL and return timestamped status, redirects, metadata, content hash, and a receipt.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| expectedText | No | ||
| expectedStatus | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the tool is clearly a safe, read-only operation. The description adds useful behavioral context beyond annotations by listing the timestamped outputs and the receipt, and the title conveys the $0.01 USDC cost. No contradiction with annotations was found.
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 description is a single efficient sentence that front-loads the core action and then lists the key outputs. There is no filler or repetitive content, and every component contributes to understanding the tool's behavior.
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?
The description provides a solid high-level overview and lists return components, but it leaves meaningful gaps: the semantics of expectedText and expectedStatus are not explained, there is no output schema to compensate, and no guidance is given for failure or mismatch behavior. It is adequate for a simple call, but not fully complete.
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 0%, so the description must compensate for the lack of parameter documentation. It only clarifies that the URL is 'one public URL' and that 'status' appears in the output, but it does not explain expectedText, expectedStatus, how they interact, or how they affect verification and resulting receipt.
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 names a specific verb ('Verify'), a resource ('one public URL'), and the expected results: 'timestamped status, redirects, metadata, content hash, and a receipt.' This clearly distinguishes it from simple checking tools like check_url or multi-URL tools like batch_check_urls.
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?
The description implies usage for a single public URL verification task, especially via 'one public URL' and 'receipt,' which hints at evidence capture. However, it does not explicitly state when to prefer this over check_url or batch_check_urls, nor does it mention exclusions like non-public URLs or invalid inputs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tool pairs have heavily overlapping purposes: check_url vs verify_web_evidence vs batch_check_urls all verify public URLs, while merchant_snapshot vs merchant_audit and payment_guard vs treasury_preflight cover very similar ground. The descriptions clarify some differences, but an agent could easily select the wrong tool when names alone are ambiguous.
All names use snake_case and are readable, but there is no consistent structural pattern. Some start with verbs (check_url, verify_web_evidence), while others are noun compounds (merchant_audit, payment_guard), and batch_check_urls places the verb in the middle. The naming is understandable but not predictable across the set.
At 8 tools, the count is reasonable and within the ideal range for a focused utility server. However, a few tools are near-duplicates of others, so the set feels slightly less well-scoped than the count alone suggests.
For the apparent niche of web3 payment preflight, merchant evaluation, and URL verification, the surface covers the core workflows well. The main gap is the lack of a more granular transaction-history or payment-execution tool, but agents can likely complete their intended tasks without dead ends.