probe
Free reachability and stale-risk probe for a public job, RFP, grant, auction, listing, pricing page, or other commercial URL before buying full verification.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Free reachability and stale-risk probe for a public job, RFP, grant, auction, listing, pricing page, or other commercial URL before buying full verification.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the probe is free and checks reachability and stale-risk, which is useful. But it does not describe what the output looks like (e.g., reachability status, stale-risk score), error behavior, or any side effects, important for an unannotated tool.
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, front-loaded sentence with zero redundancy. It leads with the purpose, lists target types, and ends with usage context, all in efficient wording. Every element earns its place.
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 tool is simple (one parameter, no output schema), but the description omits any hint of the return value or what constitutes a 'stale-risk' indication. For a probe, knowing the response format is important. It covers purpose and usage well but lacks completeness on outputs.
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 0% since no property descriptions exist, so the description must compensate. It gives context on appropriate URLs (public job, RFP, grant, etc.) which implies the format, but it does not explicitly explain the 'url' parameter beyond its type. The usage context partially fills the gap.
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 uses a specific verb ('probe') with a clear resource (public commercial URLs) and scope (reachability and stale-risk). It differentiates from 'full verification' which likely refers to the sibling verify_commercial_truth, and lists multiple URL categories, leaving no ambiguity about what the tool targets.
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 phrase 'before buying full verification' explicitly situates this as a preliminary step, giving clear context for when to use it. However, it does not name the alternative tool (e.g., verify_commercial_truth) or state when NOT to use it, leaving some inference required.
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.
Most tools have clearly distinct targets—Base reads, web research, opportunity search, and gating—but a few overlapping 'verify' and 'gate' tools could blur boundaries for an agent, especially verify_commercial_truth and verify_deadline_eligibility. Descriptions do differentiate them, so misuse is unlikely with careful prompting.
All names use snake_case and are internally consistent for the base_* cluster, but outside of that, some tool names are nouns while others are verbs (e.g., domain_intelligence, web_read, vendor_verification). This mixed convention makes it less predictable than a strict verb_noun pattern.
21 tools is on the high side of the comfortable range, but the server covers a broad scope: blockchain reads, web/content intelligence, opportunity discovery, commercial verification, and preflight gates. Each tool has a distinct role, though a few feel marginal rather than essential for a leaner setup.
The set covers the main workflows you'd expect: reading blockchain state, researching and verifying web snippets, tracking opportunities, and blocking bad actions with a fee preflight. The notable gap is an explicit execution step—there is no actual sending, bidding, or payment action beyond the x402 preflight. That is a reasonable boundary for a read/preflight tool suite.