Check the status of a lead created via request_quote.
lead_id: UUID returned by request_quote api_key: the api_key used when the lead was created
Returns JSON with status (new/contacted/won/lost), company info, contact fields, budget, timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | ||
| lead_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It correctly indicates a read operation and lists return fields. However, it does not mention error handling, non-mutating nature, or any side effects. The absence of explicit read-confirmation is a gap, but the description is adequate.
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 a single, focused paragraph with no superfluous words. It front-loads the purpose and provides parameter explanations and return structure in two concise sentences.
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 the presence of an output schema, the description covers the key aspects: purpose, parameters, and return fields. It lacks error handling details (e.g., what happens if lead_id is invalid), but for a simple read tool it is mostly complete. The sibling list provides context that this is for post-creation status checks.
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%, but the description explicitly explains both parameters: lead_id is 'UUID returned by request_quote' and api_key is 'the api_key used when the lead was created'. This adds significant meaning beyond the schema's bare type and requirement.
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 'Check the status of a lead created via request_quote', specifying the action (check), resource (lead status), and the dependency on request_quote. This distinguishes it from siblings like request_quote (creation) and other query tools.
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?
The description implies the tool should be used after request_quote by stating 'created via request_quote'. It provides clear context but does not explicitly state when not to use it or list alternatives. There is no mention of prerequisites beyond the parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes: search_companies, find_best_companies, smart_match, and contractor_recommendation all find contractors; get_company, company_portfolio, and company_deep_profile all return company details; calculate_cost and project_estimator both estimate costs. This makes it difficult for an agent to reliably choose the correct tool.
Tool names mix verb-first patterns (get_*, search_*, compare_*, calculate_*, export_*, find_*, request_*) with noun-first patterns (company_deep_profile, market_report, price_comparison, etc.). All names use snake_case, but the inconsistent verb/noun placement makes the set less predictable.
24 tools falls squarely in the 16-25 'feel heavy' range. While the server covers a broad domain (companies, projects, analytics, leads, estimation), the presence of many overlapping tools suggests the count could be consolidated without losing functionality.
The toolset covers the core domain well: searching companies and projects, retrieving full details, comparing entities, estimating costs, obtaining market analytics, and managing the lead lifecycle (request_quote -> get_lead_status). Minor gaps exist (e.g., no detailed per-review text, but that is explicitly stated as unavailable), but there are no dead ends for typical workflows.