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

Well beyond the readOnly/idempotent annotations, it discloses the evidence methodology, the capping rule when supplier_id is absent, a known limitation (tender documents not read), the epistemic framing ("treat it as evidence; the decision is your user's"), and an access prerequisite with a self-service URL. That is the behavioral context an agent needs before trusting or gating the output.

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 opening sentence front-loads the decision use case, followed by inputs, method, output, limitations and access in a logical order with almost no filler. It is dense and somewhat run-on, packing evidence sources into one long sentence, but every clause carries information.

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 five-parameter tool with an output schema, the description still explains the verdict vocabulary, the 0-1 score, signals, gaps, competition context and agent_guidance, plus auth and limitations — more than enough to call it correctly. The only gap is the unexplained preferred_language and include_original_evidence flags, which affect output shaping.

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 coverage is 0%, so the description carries the burden: it explains tender_id, supplier_id (tax id, e.g. Chilean RUT) and company_profile (sector, capabilities, brands, certifications, in the user's own words) with useful format guidance. However, preferred_language and include_original_evidence are never mentioned, leaving two of five parameters with no semantics anywhere.

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 a concrete decision task ("decide whether a tender is worth your user's time") and enumerates the evidence classes it evaluates: title/items/description matching, prior awards in the same UNSPSC category, amount versus the supplier's usual award, and prior sales to the buyer. That scope is clearly distinct from the sibling tools buyer_history, supplier_history, market_signals and get_tender_detail, which surface raw data rather than a synthesized fit verdict.

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?

Gives an explicit trigger ("use this to decide whether a tender is worth your user's time") plus a key conditional: without supplier_id the score is capped because text alone cannot prove capability, which tells the agent when the weaker mode is acceptable. It also sets a boundary ("does not read tender documents yet"). It stops short of naming sibling tools as alternatives for the sub-questions it can't answer.

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