AI-powered contractor recommendation. Finds the best matching companies based on budget, region, quality requirements. Returns ranked list with match scores.
| Name | Required | Description | Default |
|---|---|---|---|
| region | No | ||
| category | No | ||
| budget_max | No | ||
| budget_min | No | ||
| min_rating | No | ||
| need_contacts | No | ||
| need_portfolio | No |
| 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 carry the full burden. It mentions returning a ranked list with match scores but does not disclose whether the tool is read-only, potential side effects, or limitations. The behavioral disclosure is minimal.
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 extremely concise: two sentences that front-load the key purpose ('AI-powered contractor recommendation') and immediately follow with the core function and output. No unnecessary words.
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 tool has 7 optional parameters, an output schema, and many siblings, the description is somewhat incomplete. It explains basic inputs and output format but lacks details on ranking criteria, match score interpretation, and algorithm behavior. The output schema exists but the description could still provide more context.
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?
The parameter schema has 0% coverage, so the description must compensate. It mentions budget, region, and quality requirements, which map to some parameters (budget_max, budget_min, region, min_rating), but ignores others like category, need_contacts, and need_portfolio. It adds high-level meaning but not full detail.
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 the tool finds the best matching companies based on budget, region, and quality requirements, and returns a ranked list with match scores. However, it does not explicitly differentiate from similar siblings like smart_match or compare_companies, though the mention of 'AI-powered' and 'ranked list' provides some distinction.
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 offers no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. Without any usage context, the agent must infer suitability from the purpose alone.
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.