get_fix_packScan a public URL and return Fix Pack v2: prioritized fixes with stable ids, observed evidence, candidate target URLs and repository paths, review gates, and fix-specific acceptance assertions for a coding agent.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public site URL (https://example.com) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full burden. It mentions scanning a public URL and returning a structured output, but does not disclose potential behaviors such as rate limits, caching, or side effects. The lack of detail is mitigated by the read-only nature implied by 'scan'.
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 sentence that is both concise and informative. It front-loads the action ('Scan a public URL') and then details the output, making it easy to parse. No unnecessary words.
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?
Given the tool has only one parameter and no output schema, the description adequately explains the purpose and return value. It is complete enough for an agent to understand what it does, though it could mention potential failure modes or edge cases.
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 in the schema is identical to the tool description's mention of 'Public site URL'. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
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 verb 'Scan a public URL' and the resource 'Fix Pack v2', listing specific outputs like prioritized fixes, stable ids, evidence, etc. It effectively distinguishes from siblings by specifying a structured fix pack with review gates and acceptance assertions.
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 that the tool is used to get prioritized fixes from a public URL, but does not explicitly state when to use this tool versus siblings (scan_url, verify_fixes). No when-not-to-use or alternative guidance is provided.
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.