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atlas_case_study_search

Read-onlyIdempotent

Search ATLAS case studies by keyword or technique ID to find real-world AI/ML attack incidents. Control output detail with include parameter.

Instructions

Search ATLAS case studies (real-world AI/ML attack incidents) by keyword or referenced technique. Default response is SLIM (description truncated to 240 chars per row); pass include='full' for the verbose summary. Useful when the user has a technique in hand and wants to see incidents that exercised it. Drill via atlas_case_study_lookup for the full procedure list. Free: 30/hr, Pro: 500/hr. Returns {query, total, results [{case_study_id, name, description (truncated by default), techniques_used}], next_calls}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordNoSubstring match against case study name + description (case-insensitive). Min 2 chars. Example: 'evasion', 'data poisoning'. Omit to list all.
technique_idNoFilter to case studies that include this ATLAS technique id, format 'AML.T####' or 'AML.T####.###' (e.g. 'AML.T0051'). Omit for any technique.
limitNoMax results to return. Range: 1-200.
includeNoDetail level. Default ('') returns slim records (description truncated to 240 chars). Pass 'full' for full description on every row.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already provide readOnlyHint and idempotentHint. Description adds: default slim response with truncated description, include='full' for verbose, rate limits (Free 30/hr, Pro 500/hr), return structure including next_calls. No contradictions.

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?

Three-sentence description, front-loaded with purpose, dense with useful information, no wasted words.

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

Completeness5/5

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

All 4 parameters documented, return shape described (query, total, results, next_calls), sibling tools mentioned for drill-down. Complete for a search tool with read-only behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, baseline 3. Description adds value with details: keyword needs min 2 chars (not in schema example), technique_id format, limit range, include enum explanation. Exceeds baseline.

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?

Description clearly states it searches ATLAS case studies by keyword or technique, with verb 'search' and specific resource. Distinguishes from sibling tools like atlas_case_study_lookup and atlas_technique_search.

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?

Explicitly says tool is useful when user has a technique and wants incidents. Mentions drill-down via atlas_case_study_lookup for full procedure list. No explicit when-not, but provides context for use.

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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