lazaretto
Server Details
Verify a skill, tool, or package for malicious behavior before your agent installs it. Hosted.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- jamesdfinance-dev/lazaretto-mcp
- GitHub Stars
- 0
- Server Listing
- lazaretto-mcp
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Tool Definition Quality
Average 4.2/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: known_bad_lookup is a free hash check against a known-bad list, while scan_artifact is a paid deep scan. Their descriptions explicitly differentiate them, leaving no ambiguity.
Both tool names use snake_case, but 'known_bad_lookup' follows an adjective_noun_verb pattern while 'scan_artifact' follows verb_noun. Names are still readable and predictable, with only a minor inconsistency.
With only two tools, the server is minimal but appropriate for its narrow scope of malware scanning. The count is slightly thin but not unreasonable for a focused utility.
The tools cover free hash lookup and paid deep scan, but missing credit management (e.g., check balance) and scan history retrieval. The surface is functional but has notable gaps for a complete workflow.
Available Tools
2 toolsknown_bad_lookupAInspect
Check a SHA-256 against Lazaretto's known-bad indicator set (refreshed daily from abuse.ch). Free and anonymous. A miss only means this exact hash is not in the indicator set; it is not a clean verdict on the artifact.
| Name | Required | Description | Default |
|---|---|---|---|
| sha256 | Yes | 64 hex chars, optionally sha256: prefixed |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description discloses key behaviors: free, anonymous, and the semantics of a miss. It could include more details like data freshness or rate limits, but the essential safety profile is clear.
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 with no wasted words, front-loaded with the core action and followed by crucial context.
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 lookup with one parameter and no output schema, the description fully covers the tool's purpose, scope, and key limitation (miss not clean), making it complete.
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% and the description adds no extra detail about the parameter beyond what the schema provides ('64 hex chars, optionally sha256: prefixed'), meeting the baseline.
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 specific verb 'Check' and resource 'SHA-256 against Lazaretto's known-bad indicator set', clearly distinguishing it from sibling tool 'scan_artifact' which is likely broader.
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 states it's free and anonymous, and explicitly warns that a miss is not a clean verdict. This provides clear context for when to use and the limitation, but does not directly contrast with the sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
scan_artifactAInspect
Deterministically analyze a package, repo, skill, or file for malicious behavior (credential theft, data exfiltration, obfuscation, prompt injection aimed at the agent, install scripts) and return a verdict (malicious, flagged, clear, error) with the exact evidence and a hash of what was scanned. Requires prepaid credits presented as an X-API-Key request header; consumes one credit per successful scan. Buy credits at POST https://lazaretto.dev/v1/credits/topup. For a free check, use known_bad_lookup.
| Name | Required | Description | Default |
|---|---|---|---|
| ref | No | The locator: an npm spec (name@version), a GitHub repo URL, a ClawHub skill id, or a raw file URL. Omit for type=inline. | |
| type | Yes | What kind of artifact ref points at. | |
| depth | No | lookup = known-bad match only; full = full behavioral analysis. | full |
| content | No | Raw file content, required when type=inline. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses credit consumption, authentication via X-API-Key header, and return of verdict with evidence and hash. It also explains the analysis types (lookup vs full) and verdict possibilities.
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 paragraph that front-loads the purpose and adds details efficiently. It is clear and includes necessary information without unnecessary length.
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?
With no output schema, the description explains the return value (verdict with evidence and hash). It covers prerequisites, credit consumption, depth options, and alternative tool, making it fairly complete for a complex tool with four parameters.
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 the description adds minimal new parameter-level info. The ref and type descriptions in the schema are already detailed. The description does not significantly enhance parameter understanding beyond what the schema provides.
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 tool analyzes packages, repos, skills, or files for malicious behavior and returns a verdict. It lists specific behaviors (credential theft, data exfiltration) and distinguishes from sibling tool known_bad_lookup.
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 explains when to use this tool (for deterministic analysis with credits) and provides an alternative (known_bad_lookup for free checks). It also mentions prerequisites like prepaid credits and where to buy them, offering clear context.
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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{
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