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sparkvibe-io

GuardianShield

by sparkvibe-io

check_quality_gate

Evaluate code quality against configurable severity thresholds and return a pass/fail/warn verdict for CI pipeline decisions.

Instructions

Scan code and evaluate findings against configurable severity thresholds. Returns a pass/fail/warn verdict suitable for CI pipelines. Exit codes: 0=pass, 1=fail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesSource code to scan.
fail_onNoFail if any finding at this severity or above. Default: high
warn_onNoWarn if findings at this severity. Default: medium
languageNoOptional programming language hint.
file_pathNoOptional file path for context.
max_findingsNoOptional absolute cap on finding count.
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It clearly states that the tool returns a verdict (pass/fail/warn) and exit codes, which is useful for behavioral understanding. However, it does not disclose whether the tool is destructive, reads data, requires authentication, or has rate limits. For a tool that scans code, these are important but less critical than for mutation tools, so the score is slightly below a 5.

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?

The description is three concise sentences, each adding distinct value: first sentence defines the core action, second states the output verdict, third specifies exit codes. There is no redundant or wasted text.

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

Completeness4/5

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

Given the complexity (6 params, 1 required) and no output schema, the description provides the key missing piece by explaining the return verdict and exit codes. However, it does not describe what happens with the optional parameters (e.g., 'fail_on' and 'warn_on' behavior is implied but not explained), which could enhance completeness. Still, the description resolves the main gap for a tool that returns a verdict rather than raw findings.

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?

The input schema has 100% description coverage, so the schema already documents all parameters. The description adds no additional parameter-level meaning beyond what the schema provides. According to the rubric, when schema_description_coverage is high (>80%), the baseline is 3, and the description does not exceed that 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?

The description uses a specific verb phrase 'Scan code and evaluate findings against configurable severity thresholds' and explicitly distinguishes the tool's purpose from its siblings by naming the output verdict ('pass/fail/warn') and CI pipeline use case. This clearly differentiates it from scanning tools like 'scan_code' or 'scan_file' which presumably only scan without evaluating against thresholds, and from 'check_secrets' which has a narrower focus.

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 provides strong usage context by mentioning suitability for CI pipelines and specifying exit codes (0=pass, 1=fail). However, it does not explicitly state when to use this tool versus its many siblings (e.g., when to choose 'check_quality_gate' over 'scan_code' or 'scan_file'), nor does it mention exclusions or prerequisites. The CI pipeline mention is a clear use case but does not fully guide agent decision-making among alternatives.

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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