bloodhound_collect

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It warns that BloodHound collection is detectable by EDR/SIEM, generates significant LDAP traffic, requires valid credentials, and has an allowed-hosts constraint. It also notes that passwords are redacted in logs and that output is written as JSON/ZIP files, providing rich behavioral context beyond the schema.

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 well-structured and appropriately sized. It front-loads the purpose, then uses an Args list, Returns summary, and WARNING section. Every sentence adds value—no filler or repetition—and the format is scannable for an AI agent.

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 tool with 8 parameters, no annotations, and an output schema not shown, the description covers prerequisites, behavior, output, and safety warnings. It explains what the tool returns (collection summary with file locations and AD object counts) and flags operational risks, making it sufficiently complete for correct invocation and expectation setting.

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?

The input schema has 0% description coverage, but the description compensates by documenting all 8 parameters with meaningful semantics: target is a Domain Controller IP, hashes use LM:NT format, collection_method lists valid values, output_dir writes JSON/ZIP files, and timeout overrides the scan timeout. This fully bridges the schema's lack of descriptions.

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 opens with a specific verb and resource: 'Collect Active Directory data for BloodHound attack path analysis.' It further details what bloodhound-python enumerates (users, groups, computers, GPOs, trust relationships), making the tool's purpose unmistakable and distinguishing it from AD enumeration siblings like impacket_secretsdump or enum4linux_scan.

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 provides clear context for when this tool is appropriate: it maps attack paths to Domain Admin and requires valid domain credentials. It also includes operational prerequisites such as the target being in tengu.toml allowed_hosts. However, it does not explicitly name alternatives or state when not to use this tool, so it misses the top tier for usage guidance.

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