validate_agent_cardValidates a pasted /.well-known/agent-card.json against the nine fields A2A marks required and each skill's id/name/description/tags, and warns on capabilities declared true that a reader will then try. Example: json='{"name":"a"}' returns the eight missing fields.
| Name | Required | Description | Default |
|---|---|---|---|
| json | Yes | The agent card JSON itself, not a URL. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavior beyond that: it checks specific required fields, validates each skill's fields, and warns about capabilities declared true, with a concrete example of the missing-fields result. No contradiction with annotations.
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?
Two dense sentences plus one illustrative example, with the core validation behavior front-loaded and no redundant words. The example is small and earns its place by showing the missing-fields 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?
For a single-parameter validation tool with strong annotations, the description covers the validation scope, skill checks, capability warnings, and a behavioral example. It does not detail the full return/error format, but that is a minor gap given the tool's simplicity and the absence of an output schema.
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%, and the parameter description already states that 'json' is the agent card JSON itself, not a URL. The description reinforces this with 'pasted' and an example, but it does not add substantial new parameter semantics beyond the schema.
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?
Names a specific verb ('Validates'), a concrete resource ('a pasted /.well-known/agent-card.json'), and the exact validation criteria (nine A2A required fields plus skill id/name/description/tags). This clearly distinguishes it from sibling validation tools targeting other document types.
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 makes the intended use case clear: a pasted agent-card JSON string, not a URL. It implies this is for inline validation rather than fetching or explaining external documents, though it does not explicitly name alternatives or exclusions.
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.
Each tool has a distinct purpose: live host probing, catalogue explanation, llms.txt generation, agent card validation, and llms.txt validation. Even check_discovery_documents and explain_document are clearly separated as 'probe a host' versus 'look up a catalogue entry.'
Most tools follow a clear verb_noun pattern like check_discovery_documents, explain_document, and validate_agent_card. However, llms_txt_from_sitemap breaks the pattern by being a noun phrase with no verb, making it slightly inconsistent.
Five tools is well-scoped for a specialized agent discovery auditing server. Each tool earns its place and there is no obvious redundancy or bloat.
The set covers the core workflows: auditing hosts, explaining documents, and validating two key formats. Minor gaps exist, such as no generator for agent cards or validators for the other 20 probed document types, but agents can still accomplish the main purpose.