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

With no annotations, the description supplies the behavioral profile: it computes from historical award/budget ratios, auto-selects a comparison baseline by sample sufficiency with an explicit priority order, and returns three tiers of advice. It doesn't address read-only behavior or auth/rate limits, but for a pure analysis tool those are less material.

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 text is compact and front-loaded with purpose. Every clause contributes: outcome, methodology, baseline priority, and use cases. There is no fluff or repetition.

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?

The description covers what the tool is for, how it works, and when to use it, and names the output form as three bid tiers. However, with no output schema and no parameter explanations, the exact return structure and how to resolve the two ID parameters are left to inference.

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 0% and the description never explicitly maps unit_id/job_number to their roles. Only indirect context ('這個案子', '同機關') hints that job_number identifies the case and unit_id identifies the agency, which is insufficient given the low coverage.

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 opens with a concrete prediction target ('這個案子大概會以多少錢成交') and states the deliverable: three bid-suggestion tiers derived from historical award/budget ratios. This makes it clearly an analysis/inference tool rather than a retrieval or vendor-comparison tool, so it is distinguishable from siblings like search_tenders or compare_vendors.

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?

It explicitly says this is for when the user asks '這案該報多少' or '值不值得投', providing a clear trigger condition. It does not state exclusions or name alternative tools, so it stops short of a 5.

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