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Moltline Code Review & AI-Code Verifier

Security Deep Dive

security_deep_dive
Read-onlyIdempotent

Run an OWASP-oriented security pass over a source file. PREMIUM (license).

Checks injection sinks, auth/session handling, crypto misuse, SSRF/deserialization, and unsafe file/path handling — each finding cites the line, the OWASP risk class, and a concrete fix direction. Typical input {"code": ""} returns {"issues": N, "findings": [{"line": N, "class": "A03 Injection", "fix": "...", "code": "..."}], "owasp_note": "..."}.

Use on one source file when vulnerabilities are the question. Not for style or structure (complexity_report), and never a substitute for a security professional on high-risk code. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesFull source text to audit, pasted as a single string; any common language.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true and idempotentHint=true. The description reinforces these by stating 'Every call is read-only and idempotent.' It adds valuable context beyond annotations: error handling (returns error objects instead of protocol errors), licensing (PREMIUM), and retry safety. No contradictions. Minor gap: does not describe rate limits or specific authentication needs.

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

Conciseness5/5

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

The description is efficiently structured: first sentence states purpose, then lists checks, provides input/output example, usage guidance, error handling, and idempotency statement. Every sentence adds value with no repetition or fluff. Front-loaded with the core action.

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

Completeness5/5

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, full schema coverage, annotations covering idempotency and read-only, and an output schema exists (though not provided in full), the description compensates by showing the output shape. It also covers licensing, error handling, and usage boundaries. No obvious gaps for an agent to select and invoke correctly.

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

Parameters4/5

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

Schema coverage is 100% with a single parameter 'code' described as 'Full source text to audit...'. The description adds significant meaning beyond the schema by providing an example input/output format ({'code': '<file contents>'}) and showing the expected return structure with fields like issues, findings, owasp_note. This helps the agent understand how to construct the input and interpret results, which is not in the schema alone.

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

Purpose5/5

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

The description clearly states the tool runs an OWASP-oriented security pass on a source file, lists specific checks (injection, auth, crypto, etc.), and differentiates from sibling 'complexity_report' by specifying it is not for style or structure. This provides a specific verb+resource with clear scope.

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

Usage Guidelines4/5

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

The description explicitly says 'Use on one source file when vulnerabilities are the question' and warns 'Not for style or structure (complexity_report)' and 'never a substitute for a security professional on high-risk code.' It also explains error behavior and retry safety. However, it does not mention alternative siblings like secret_scan or ai_code_smell_scan, leaving some gaps in tool comparison.

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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TDQS

A4.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: AI smell detection, structural complexity, persona loading, checklist generation, diff risk scanning, secret scanning, and security deep dive. No two tools overlap in function, and descriptions explicitly state what each should not be used for.

Naming Consistency4/5

All tool names use snake_case and are readable. However, the pattern varies: some are verb_noun (get_reviewer_persona, secret_scan) while others are noun phrases (complexity_report, review_diff). This minor inconsistency prevents a perfect score.

Tool Count5/5

Seven tools cover the code review domain well without being excessive. Each tool addresses a specific aspect of code quality, security, and AI authorship detection. The scope is focused and no tool seems superfluous.

Completeness4/5

The tool set covers most analysis needs for code review: full-file scans, diff analysis, secret detection, security audit, and context like persona and checklist. A minor gap is the lack of an aggregation tool to combine results into a unified review report, but the core analysis workflows are complete.

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