detect_patterns

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

The description adds context beyond the readOnlyHint and openWorldHint annotations by detailing the algorithmic methods (NER, date patterns, TF-IDF) and explicitly stating 'No AI calls.' It could mention potential limitations or output size, but overall provides good behavioral insight.

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 concise at three sentences, with the key purpose front-loaded. Every sentence adds value: first sentence defines scope, second details returns, third mentions additional detection and method. No superfluous words.

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 no output schema, the description adequately explains return values (structured experience entries with titles, organizations, technologies, achievements) and mentions career progression trajectory. It could be more complete by specifying the return format or including other detected elements like metrics, but it covers essential expectations.

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?

With 100% schema coverage and a single parameter described as 'The raw text content of a resume,' the description adds no additional meaning beyond confirming the input is resume text. The baseline of 3 is appropriate as the schema already covers semantics adequately.

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 clearly states the tool detects and structures date ranges, metrics, sections, and work experience from resume text. It specifies the methods (NER, date patterns, TF-IDF) and differentiates from siblings by noting 'No AI calls,' making the purpose distinct among sibling tools like parse_resume or extract_experience_structured.

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?

While the description implies usage for algorithmic extraction without AI, it does not explicitly state when to use this tool versus alternatives. There is no mention of when not to use it or which sibling tools to prefer in different contexts, leaving the agent to infer usage from the description alone.

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