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taint_analysis

Read-onlyIdempotent

Track untrusted data from sources like HTTP params to dangerous sinks such as SQL queries. Reports unsanitized flows with CWE IDs and fix suggestions for security triage.

Instructions

Track flow of untrusted data from sources (HTTP params, env vars, file reads) to dangerous sinks (SQL queries, exec, innerHTML, redirects). Framework-aware: knows Express req.params, Laravel $request->input, Django request.GET, FastAPI Query(), etc. Reports unsanitized flows with CWE IDs and fix suggestions. Type-aware: flows that terminate at a provably non-string value (numeric/boolean coercion such as Math.floor(), (int) casts, comparison results) are pruned, since a string-injection sink cannot be exploited by a number/boolean. Heuristic, regex-based intra/inter-procedural analysis — not a sound dataflow engine; treat results as triage. Use for data-flow security analysis. For pattern-based OWASP scanning use scan_security instead. Read-only. Returns JSON: { flows: [{ source, sink, path, sanitized, cwe, suggestion }], total }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax flows to return (default: 100)
scopeYesDirectory to scan (default: whole project)
sinksNoFilter by sink kinds (default: all)
sourcesNoFilter by source kinds (default: all)
include_sanitizedNoInclude flows with sanitizers (default: false)
Behavior5/5

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

Annotations already indicate read-only and idempotent. Description adds significant behavioral details: heuristic regex-based analysis (not sound), type-aware pruning for non-string values, framework awareness, and that unsanitized flows are reported with CWE IDs and fix suggestions. No contradiction with annotations.

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 detailed but well-structured, with the core purpose first. It covers all key aspects without being overly verbose. A slight reduction in length could improve conciseness, but it remains efficient.

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?

The description explains the output format clearly, including the structure of the JSON response. It also clarifies the tool's limitations and behavior (type-aware, heuristic). With no output schema, this provides sufficient completeness for an agent to understand the tool's capabilities.

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 description does not need to add parameter details. The description does not provide additional meaning beyond the schema's descriptions. However, it gives context on how parameters like 'sinks' and 'sources' filter results, but that is evident from the enum values.

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's purpose: tracking untrusted data flow from sources to sinks for security analysis. It provides concrete examples of sources and sinks, and distinguishes it from sibling tool 'scan_security' for pattern-based scanning.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use (data-flow security analysis) and when not to use (pattern-based OWASP scanning, for which scan_security is recommended). Also advises that results are heuristic and should be treated as triage, setting proper expectations.

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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