Free security scan for AI-written GitHub repos: leaked keys, .env, eval, SQLi, CORS.
Scored across 1 tool
With only one tool in the set, there is no possibility of misselection or overlapping purpose. The single tool's intent (scan a repo for risky patterns) is unambiguous.
The lone name scan_repo follows a clear verb_noun convention that would scale predictably if more tools were added. No mixed conventions to worry about.
A single tool is thin even for a narrowly scoped scanner; there is no separate way to configure scan depth, retrieve past results, or explain findings. It is defensible as a one-shot service, but it sits at the borderline of the 1-2 tool range.
The core scan workflow is covered end-to-end, but the surface has notable gaps: no way to fetch or filter a prior scan's findings, no rule/severity configuration, and no diffing against a baseline. Agents must consume whatever the single call returns with no follow-up operations.
Scan a public GitHub repo (owner/repo or URL) for leaked secrets, .env files, eval, SQLi, CORS and other risky patterns common in AI-written code.
| Name | Required | Description | Default |
|---|---|---|---|
| repo | Yes | owner/repo or https://github.com/owner/repo |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It scopes the operation to public repos and implies a read-only scan by using 'Scan' and listing detected patterns, but it does not explicitly confirm read-only behavior, describe permissions or rate limits, or explain whether any data is stored or returned. This provides partial transparency but leaves meaningful gaps.
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 efficient sentence that front-loads the action and resource, then lists the risky patterns. Every clause contributes useful information without repetition or filler.
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 simple one-parameter tool, the description clearly covers purpose and input requirements, which is enough to invoke it at a basic level. Because there is no output schema, however, it could say more about what the scan returns or any limitations, leaving the definition minimally complete rather than fully self-sufficient.
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%, so the single 'repo' parameter and its accepted formats are already fully documented in the schema. The description restates that it accepts an owner/repo or URL but adds no syntax or validation details beyond what the schema provides; the baseline of 3 is therefore 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 uses a specific verb ('Scan') and resource ('public GitHub repo') and enumerates the exact risk categories it looks for, including leaked secrets, .env files, eval, SQLi, and CORS. This makes the tool's function immediately clear; there are no sibling tools to confuse it with.
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?
It specifies that the repo must be public and gives accepted input formats (owner/repo or URL), which gives useful context for invocation. However, it does not explicitly state when to use this tool, when not to use it, or any prerequisites; with no sibling tools, there is no alternative routing to explain, but the guidance remains implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
scan_repoFree passive security scan for AI-built apps: leaked API keys, public .env files, security headers
Security scans for AI-built apps: leaked keys, open Supabase RLS, vulnerable packages, live sites.
Security scanner for AI-written code: SAST, secrets, dependencies, IaC, containers and DAST.
Independent security review for AI-built apps: exposed secrets, broken auth, unsafe data access.
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