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lint_report

Run static-analysis lint rules on .rdl files to detect v0.2/v0.3 bug classes like multi-value-eq and dangling-embedded-image. Returns issues with severity, rule, location, message, and suggestion. Optionally select specific rules by name.

Instructions

Run static-analysis lint rules against an .rdl. Sixteen rules cover the v0.2/v0.3 sweep bug classes (multi-value-eq, missing-field-reference, dangling-embedded-image, pbidataset-at-prefix, parameter-layout-out-of-sync, double-encoded-entities, stale-designer-state, tablix-span-misplaced, dataset-fields-out-of-sync, etc.). Returns {issues, rules_run} with each issue {severity, rule, location, message, suggestion?}. Optional rules selects a subset by name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
rulesNoOptional subset of rule names; default runs all 16.
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 describes the return format {issues, rules_run} with issue fields, and mentions the optional rules parameter. It does not explicitly state read-only, but 'lint' implies non-destructive analysis.

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 concise, front-loaded with the main action, and efficiently lists the rules in a parenthetical. It could be more structured but is clear and without waste.

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 no output schema, the description adequately covers return format, parameters, and rule list. It lacks mention of error conditions or performance, but for a lint tool the provided info is sufficient for an AI to invoke it correctly.

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 50% (only rules has description). The description adds meaning by explaining that path refers to an .rdl file and that rules selects a subset. It also lists the specific rule names, adding value beyond schema.

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 explicitly states 'Run static-analysis lint rules against an .rdl', providing a specific verb and resource. It enumerates the rule categories, distinguishing itself from sibling tools which are all add/set/get operations.

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 clearly explains what the tool does and the optional rules parameter, but does not explicitly state when to use it versus alternatives. Since no sibling tool performs linting, the context is still clear.

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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