huggingface_proofer

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile of this external read operation is fully covered structurally. The description adds that it inspects only *public* data and that it performs cross-referencing, but says nothing about authentication requirements, HF rate limits, or behavior when a profile/handle cannot be resolved — a real gap for an open-world external lookup.

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?

Two dense sentences with the core action front-loaded ('Inspect a candidate's public Hugging Face profile') followed by the verification purpose. No filler or repetition, though the parenthetical claim list is slightly list-heavy for a two-sentence description.

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?

There is no output schema, so the description carries the burden of explaining what comes back; it gestures at this ('verifiable Hugging Face model weights, spaces, and real-world downloads') but never describes the response shape, scoring, or handling of unverifiable claims. Adequate for a simple two-param tool, but thin for a verification tool with no structured output contract.

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?

Schema description coverage is 100%, so both parameters are already documented (handle/URL/resume text, and the optional claims list). The description indirectly explains what ai_technical_claims is for by enumerating claim categories (LoRA, GGUF, Quantization), but adds no format or syntax detail beyond the schema. Baseline 3 applies.

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?

States specific verbs (Inspect, Cross-references) and resources (Hugging Face profile, models, spaces, datasets), and enumerates the claim types it validates (fine-tuning, LoRA, GGUF, Quantization, Legal AI). It names the domain explicitly, but never distinguishes itself from the near-identical sibling github_proofer, leaving the agent to infer which proofer applies to which artifact.

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 implied by 'Cross-references GenAI resume claims ... with verifiable Hugging Face model weights' — i.e., use this to verify a candidate's HF presence against resume claims. However, no explicit when-to-use, when-not-to-use, or alternative (e.g., github_proofer for repos, evidence_validator for general claims) is given, so routing between siblings is left to inference.

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