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conventions

Retrieve project-specific coding practices before writing new code. Filter by project or area to align with existing architecture, testing, and naming patterns.

Instructions

Before writing new code, check how this codebase does things. Retrieves stored conventions, optionally filtered. Example: {"lobe": "my-project", "area": "testing"} or {"lobe": "my-project"} for all. recall() also surfaces conventions. Use this for focused convention lookup, recall() for broader cross-topic search.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaNoOptional keyword filter (e.g. "testing", "naming", "architecture").
lobeNoMemory lobe name. No lobes configured yet — run memory_bootstrap(lobe: "your-project", root: "/absolute/path/to/repo") first.
Behavior3/5

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

With no annotations, the description must carry the full burden of behavioral disclosure. It states the tool 'retrieves' conventions and gives filter examples, which implies a read-only operation. However, it does not explicitly state that it is non-destructive, nor does it mention dependence on memory_bootstrap or behavior when no conventions match. Missing explicit side-effect or prerequisite details beyond what's implied.

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 concise, front-loaded with the key purpose, and includes a compact example. It avoids redundancy and every sentence contributes: usage context, retrieval mechanics, example, and alternative tool guidance.

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?

For a simple read tool with two optional params and no output schema, the description covers when, what, and how, plus an alternative. It doesn't detail return values, but schema covers parameter specifics. The main gap is lack of mention of the need for memory_bootstrap (though in schema), but overall adequate for the complexity.

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 description coverage is 100%, so the baseline is 3. The description adds value by showing concrete examples of parameter combinations, clarifying that omitting 'area' returns all conventions for a lobe. This enhances the semantic understanding of how the parameters combine.

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 retrieves stored conventions, with a specific context of use ('Before writing new code'). It distinguishes from recall() by noting this is for focused lookup, which is an explicit alternative. The verb 'Retrieves' and resource 'stored conventions' make the purpose unambiguous.

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?

The description explicitly says when to use ('Before writing new code') and provides an alternative: 'recall() for broader cross-topic search.' This qualifies as explicit when/alternatives, exceeding the minimum requirement.

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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