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Two tools with minimal but present definitions. Both have clear verb-noun naming (add_tool, slugify_tool) and basic descriptions (10-30 chars). Input schemas are visible with typed parameters and descriptions. However, descriptions are extremely terse (below the 50-200 char LLM-optimized baseline), lack context on WHEN to use each tool, and provide no error guidance. No output schema documentation. No parameter constraints (e.g., numeric ranges for add_tool). Tools are simple utilities with low complexity, but fall short of production-grade quality due to sparse documentation and missing error handling patterns.
Add two numbers and return the result.
Convert text into a URL-safe slug.
Descriptions are too terse (10-30 chars vs. 50-200 char baseline). 'Add two numbers and return the result' and 'Convert text into a URL-safe slug' lack context on when to use each tool, expected input ranges, or output format.
No output schema documented. LLMs cannot plan downstream tool calls or extract results without knowing the return type structure. Both tools return simple scalars (float, string) but this is not explicitly stated.
No parameter constraints. add_tool accepts float a and b with no min/max bounds, LLMs could pass absurdly large numbers. slugify_tool accepts any string with no length limit.
No error handling guidance. Tools provide no recovery hints if inputs are invalid or operations fail. LLMs have no actionable next steps on error.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 47 | 2026-07-28+ | v2 |
Tool names use '_tool' suffix, which is redundant and non-standard. Prefer 'add' and 'slugify' directly, or use verb_noun pattern like 'compute_sum' and 'create_slug'.