find_ai_related_scripts

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

With no annotations, the description carries the full burden. It discloses what counts as a match (a useful behavioral detail) but says nothing about whether the scan is regex- or literal-based, whether matches come from comments/strings as well as code, or any cost/limit on a whole-project scan.

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?

A single front-loaded sentence with an efficient colon-delimited pattern list. No filler, no restatement of the title, and the pattern enumeration earns its space by defining match criteria.

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?

For a simple no-arg read tool this is close, but with no output schema the description should say what comes back (script paths only, or paths plus matched lines/snippets) and roughly how broad the scan is. Without that, an agent cannot predict result shape before calling.

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?

Zero parameters, so there is nothing to disambiguate; the description implicitly establishes project-wide scope. Baseline 4 applies for a parameterless tool, with no contradictory scoping claims.

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?

"Scan C# scripts for AI/ML patterns" gives a specific verb (scan) and resource (C# scripts), then enumerates the concrete patterns detected (Sentis, ML-Agents, NavMesh, behavior trees, ONNX, LLM API strings). This separates it from content-agnostic siblings like list_scripts or find_scripts_by_content, though it never names an explicit alternative.

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?

Usage is only implied: an agent can infer it should call this when hunting for AI-related code. There is no statement of when NOT to use it, nor any pointer to get_ai_ml_package_inventory or find_scripts_by_content as the package-level or generic-content alternative.

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