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Identify digital fingerprints by passively examining pre-collected HTTP headers, HTML source, or service banners.

Instructions

Passive analysis of pre-collected data. No network calls. Supports three modes: headers (HTTP header fingerprinting), html (HTML source analysis), banner (service banner identification).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoURL context for headers/html analysis
htmlNoHTML source code (for type=html)
portNoPort number context for banner analysis
typeYesAnalysis type
bannerNoService banner string (for type=banner)
headersNoHTTP response headers (for type=headers)
Behavior3/5

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

Without annotations, the description carries the full burden. It clearly states the tool is passive and makes no network calls, which is transparent. However, it does not disclose error handling, return format, or edge cases, which would be helpful for a multi-mode analysis tool.

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 extremely concise: two sentences that cover purpose, behavioral trait, and the three modes. Every word earns its place with no fluff or redundancy.

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?

Given the tool has 6 parameters, nested objects, and no output schema, the description is too minimal. It does not explain what each analysis mode returns or provide guidance on expected output, which is necessary for an agent to use the tool effectively without external documentation.

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 baseline is 3. The description reinforces the parameter roles by grouping them under the three modes, but does not add significant new meaning beyond the schema descriptions. It clarifies which parameters apply to which mode, which is helpful but not enough to raise the score.

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 performs passive analysis of pre-collected data, which is a specific verb+resource. It also lists three distinct modes (headers, html, banner), effectively distinguishing it from sibling tools that likely involve active scanning or other operations.

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 indicates the tool is for passive analysis without network calls, implying when to use it (pre-collected data). However, it does not explicitly mention when not to use it or suggest alternative tools, though the sibling context provides some implicit differentiation.

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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