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cortex_analyze_observable

Run security analyzers on an observable (IP, domain, hash, etc.) and collect aggregated results with taxonomy summary. Supports auto-detection of data type.

Instructions

Run applicable analyzers against an observable and collect aggregated results with taxonomy summary. Can auto-detect data type. By default only an explicit allowlist of analyzers runs; set fanOut=true to submit to every applicable analyzer (capped by CORTEX_MAX_FANOUT). Fanning out submits the observable to many third-party services (SSRF-by-proxy / IOC disclosure / quota burn), so it is opt-in.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
papNoPermissible Actions Protocol level (0-3). Default: 2
tlpNoTraffic Light Protocol level (0=WHITE, 1=GREEN, 2=AMBER, 3=RED). Default: 2/AMBER
dataYesThe observable value (IP, domain, hash, URL, email, etc.)
fanOutNoIf true, submit the observable to ALL applicable analyzers (capped by maxAnalyzers / CORTEX_MAX_FANOUT). Default false: you must pass an `analyzers` allowlist.
timeoutNoTimeout in seconds per analyzer (default: 300)
dataTypeNoThe observable data type. If omitted, will be auto-detected from the value.
analyzersNoExplicit allowlist of analyzer names (substring match, case-insensitive) to run. Required unless fanOut=true. Only matching analyzers that also support the data type are submitted.
maxAnalyzersNoHard cap on how many analyzers to run this call. Defaults to and is clamped by the server's CORTEX_MAX_FANOUT (default 10).
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses auto-detection, the allowlist vs fan-out behavior, risks of fan-out (SSRF, IOC disclosure, quota burn), and the cap via CORTEX_MAX_FANOUT. It does not describe the return value structure or error handling.

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

Conciseness4/5

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

The description is two sentences long and packs essential information without fluff. The first sentence is dense but covers the core purpose and key features.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 parameters and no output schema, the description does not detail the return value format (only mentions 'aggregated results with taxonomy summary'). It also omits behavior for timeouts or error handling. However, the schema and annotations cover many aspects, making it adequate.

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 coverage is 100%, so baseline is 3. The description adds context about fanOut risks and auto-detection, but the schema already explains the parameters well. The added value is marginal.

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 verb 'Run analyzers' and the resource 'observable'. It mentions 'aggregated results with taxonomy summary', which distinguishes it from sibling tools like cortex_run_analyzer that run a single analyzer.

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 contrasts the two modes: 'only an explicit allowlist' vs 'fanOut=true', and explains that fanning out is opt-in due to third-party risks. It does not, however, explicitly recommend when to use this tool over sibling tools like cortex_run_analyzer.

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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