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import_static_analysis

Import a SARIF 2.1.0 report to preserve immutable analysis artifacts and store source-scoped static candidates validated against a project root.

Instructions

Preserve one native SARIF 2.1.0 report and project bounded static candidates.

The native report remains an immutable analysis-result artifact. Static candidates are source-scoped analyzer output, not Findings or confirmation of runtime behavior.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesSARIF report path relative to the fixed project root, or an absolute path already inside it.
sensitivityNointernal
source_rootNoExisting source directory relative to the fixed project root. Every normalized SARIF location is validated against this exact root..
exclude_pathsNo
include_pathsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

B3.1/5.0
Behavior3/5

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

Annotations mark this as non-read-only and non-idempotent, but don't describe side effects. The description adds useful context: the native report stays immutable and candidates are source-scoped, not runtime findings. However, it doesn't disclose behavior on repeated imports, overwrites, or validation failures.

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 compact and front-loads the main purpose, with a second sentence that adds an important semantic clarification. It is appropriately sized, though wording like 'immutable analysis-result artifact' is slightly more formal than necessary.

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?

For a mutation/import tool with five parameters, the description doesn't explain normalization rules, how source_root validation behaves, how include/exclude_paths interact, or what happens on duplicate imports. The output schema may help, but the prose alone leaves too many invocation-relevant details unspecified.

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

Parameters2/5

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

Schema description coverage is only 40%, covering path and source_root, while sensitivity, include_paths, and exclude_paths lack descriptions in both schema and prose. The description loosely maps 'SARIF report' to path and 'project bounded' to root validation, but it does not clarify filtering or sensitivity parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete action ('Preserve') and resource ('native SARIF 2.1.0 report and project bounded static candidates'). It clearly separates static-analysis candidates from Findings or runtime-behavior artifacts, which helps distinguish this tool from many extract_* and finding-related siblings.

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

Usage Guidelines3/5

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

The description implies this tool is for ingesting native SARIF 2.1.0 static-analysis output, and the 'not Findings' caveat provides some comparative guidance. However, it never explicitly says when to prefer this over siblings like import_artifact or when NOT to use it, leaving routing partially to inference.

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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