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edict_lint

Analyze Edict code AST to detect quality issues like unused variables, missing contracts, oversized functions, and redundant effects without blocking compilation.

Instructions

Run non-blocking lint analysis on an Edict AST. Returns quality warnings (unused variables, missing contracts, oversized functions, redundant effects, etc.) without blocking compilation. Warnings use the same structured format as errors but with severity: 'warning'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
astYesThe Edict JSON AST to lint
Behavior4/5

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

With no annotations provided, the description carries the full burden and does so well by disclosing key behavioral traits: it's non-blocking (implying asynchronous or quick operation), returns warnings in a structured format similar to errors with severity 'warning', and lists example warning types (e.g., unused variables). It does not mention rate limits or authentication needs, but for a linting tool, this is generally acceptable.

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 front-loaded with the core purpose in the first sentence, followed by essential details about output format. Every sentence adds value—no wasted words—making it efficient and easy to parse for an AI agent.

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 tool's moderate complexity (linting analysis), no annotations, and no output schema, the description is quite complete: it explains the purpose, behavior, and output format. However, it could slightly improve by hinting at error handling or performance characteristics, but it's largely sufficient for effective use.

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, with the 'ast' parameter fully documented in the schema. The description adds no additional meaning beyond the schema, such as format details or constraints for the AST, so it meets the baseline of 3 where the schema does the heavy lifting.

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 specific action ('Run non-blocking lint analysis'), the target resource ('an Edict AST'), and distinguishes it from siblings by specifying it returns quality warnings without blocking compilation, unlike tools like edict_compile or edict_check which likely involve compilation or validation.

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?

It provides clear context for when to use this tool ('without blocking compilation'), implying it's for preliminary analysis rather than full validation or compilation. However, it does not explicitly state when not to use it or name specific alternatives among the many sibling tools, such as edict_check or edict_validate.

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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