verify_fixesRe-scan a public URL and evaluate fix-specific stable ids from a previous v1 or v2 Fix Pack. A fix closes when its finding id is absent; score delta is secondary evidence only.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public site URL (https://example.com) | |
| previous_fix_pack | Yes | The Fix Pack returned earlier by get_fix_pack (or an object with {score, fixes:[{id}]}). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It explains the core behavior: re-scanning, evaluating stable IDs, and closure logic (finding id absent vs score delta). However, it does not disclose side effects, required permissions, rate limits, or error conditions—details important for tool invocation.
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 sentences, no redundancy. The first sentence states the verb and resource, the second clarifies key nuance. Every word earns its place, and the structure is front-loaded with the primary action.
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 moderately complex (re-scan, evaluation, fix closure logic) and has no output schema, yet the description does not explain the return format, structure, or next steps. The agent lacks information on what to expect after invocation, making the description incomplete.
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 baseline is 3. The description adds some context: 'previous v1 or v2 Fix Pack' and 'stable ids', which provides meaning beyond the schema. However, it does not elaborate on param syntax or constraints, making the addition modest.
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 clearly states the action: 'Re-scan a public URL and evaluate fix-specific stable ids from a previous v1 or v2 Fix Pack.' It also explains what constitutes a fix close, which differentiates it from siblings like scan_url (general scan) and get_fix_pack (retrieve pack).
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 after obtaining a previous Fix Pack, but does not explicitly state when to prefer this over siblings (e.g., scan_url, get_fix_pack). No alternatives or exclusions are provided, leaving usage context somewhat vague.
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 target clearly distinct artifacts: OpenAPI, A2A cards, crawler access, saved reports, and fix verification. The main ambiguity is between scan_url and get_fix_pack, since both scan a public URL and return fix-pack-related output, though scan_url emphasizes the full score/findings while get_fix_pack focuses on prioritized fixes.
All tool names follow a consistent verb_noun snake_case pattern: audit_, check_, get_, scan_, validate_, verify_. The verbs are appropriate and the naming makes the intended action readable at a glance.
Seven tools is well-scoped for a URL and API readiness scanning server. Each tool addresses a distinct phase or artifact in the workflow: scanning, fix generation, fix verification, report retrieval, and specialized static audits.
The core lifecycle is covered: scan a URL, obtain fixes, verify fixes, and retrieve reports, plus specialized audits for OpenAPI, A2A, and crawler access. Minor gaps exist, such as no way to list or manage saved public reports and no explicit repository-connection tool, but these are workable.