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bugscan-mcp

analyze_code

Discover the BugScan paid code analysis API contract. Use the HTTP analyze endpoint for actual review execution and billing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesJava source code to review. Provide the complete file content as a single UTF-8 string.
filenameYesSource file name to review, including the file extension, for example UserController.java.
languageYesProgramming language of the submitted code. Currently, use 'java' for Java or Spring Boot source files.
requesterNoOptional caller identity recorded in audit logs, such as an agent name, service account, or end-user identifier.
repositoryNoOptional repository, service, or project identifier used to label the analysis request and audit trail.
rule_profileNoRule set profile. Use 'default' for the full rule set, 'quick' for error-focused checks, or 'security' for security-only checks.default

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It adds a useful hint that the API is 'paid' and tied to 'billing,' but says nothing about authentication, rate limits, whether the call is read-only, or what the invocation returns – a significant gap for a 6-parameter tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with no padding, and the core claim is front-loaded. But the brevity is achieved at the cost of clarity and completeness, so it reads as under-specified rather than efficiently concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema and the description never explains what the tool returns (contract fields? a URL?) even though it hints the real work happens elsewhere. For a tool with 6 parameters and 3 required inputs, this leaves an agent unable to predict the result of a call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so every parameter (code, filename, language, requester, repository, rule_profile) is already documented in the schema, including the rule_profile enum meanings. The description adds no parameter-level meaning beyond that, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a verb and resource ('Discover the BugScan paid code analysis API contract'), so it isn't a tautology. However, it clashes with the tool name 'analyze_code' and the schema (which expects actual code, filename, language) – an agent can't tell whether the tool performs analysis or merely returns a contract. The purpose lands as vague/ambiguous rather than specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It does provide a routing hint by stating the actual review is done via the 'HTTP analyze endpoint' rather than this tool. But it never says when to call this tool versus that endpoint in concrete terms, nor what triggers a need for the contract, leaving usage only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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