Recommend open-source solutions

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

With no annotations provided, the description carries the behavioral disclosure burden. It tells the agent that recommendations are evidence-backed and that outputs are repositories/workflows, but it does not explain how recommendations are produced, what limits or failures may occur, or any caveats about the evidence sources.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence that front-loads the key action and output. There is no filler, repeated boilerplate, or unnecessary structure.

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

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

Given the simplicity of the tool (two parameters, no nested objects, no output schema), the description provides adequate context for invocation: input is a problem statement, output is repositories/workflows. It could be more complete by describing the result format or evidence presentation, but the core usage is readable.

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

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

The input schema already covers both parameters well (100% coverage), giving a baseline of 3. The description adds extra meaning by making clear that the query should be a concrete engineering or content-production problem rather than a generic keyword lookup, which helps an agent phrase the query effectively.

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

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

The description uses a specific verb ('find') with a clear resource ('repositories and workflows') and a clear target scenario ('a concrete engineering or content-production problem'). It communicates the tool's function well, though it does not explicitly contrast against sibling tools like atlasrepo_search_tools or atlasrepo_get_repository.

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

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

The description provides a clear use context: use this when you have a concrete problem or outcome and want evidence-backed repository/workflow recommendations. It does not provide when-non-to-use guidance or explicitly name alternatives, so it stops short of a top score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.