Read a project, its current immutable-capable revision, requirements, artifacts, BOM summaries, and validation history.
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| project | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safe-read nature is covered. The description adds context about the 'current immutable-capable revision' and 'validation history', which are behavioral details beyond the annotations. However, it does not disclose behavior around errors, permissions, or rate limits, leaving some transparency gaps.
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, front-loaded sentence that lists all returned components without wasted words. It is concise and well-structured, earning full marks.
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, robust annotations, and only one parameter, the description provides adequate context for a safe read operation. It clearly enumerates the scope of returned data. It doesn't mention prerequisites or edge cases, but the annotations and simple parameter make this acceptable. The description is complete enough for a straightforward getter.
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 does not mention project_id at all. The parameter's meaning is only implicit from the tool name and the pattern in the schema. Since the description fails to compensate for the lack of schema documentation, the parameter semantics receive a low score despite the parameter being self-descriptive.
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 verb 'Read' and the resource 'project', enumerating the specific subcomponents (immutable-capable revision, requirements, artifacts, BOM summaries, validation history) that distinguish it from siblings like get_bom or list_project_validations. This is a precise, resource-specific statement of purpose.
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 when to use the tool: when you need a comprehensive project read including multiple related entities. However, it provides no explicit guidance on alternatives or exclusions, such as noting that get_bom provides full BOM details or list_project_validations provides validation history. The usage context is clear but not explicitly contrasted with sibling tools.
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.
Every tool targets a distinct resource, role, or action. For example, list_orders versus list_supplier_orders clearly separates buyer and supplier views, and update_supplier_order versus update_supplier_order_issue versus update_supplier_order_return handle different concerns despite similar names. Rich descriptions eliminate ambiguity.
All tool names consistently use snake_case with a verb_noun pattern (e.g., create_project, list_orders, update_supplier_capabilities, search_products). The style is uniform across reads, writes, lists, and searches, making the API predictable.
With 55 tools, the server far exceeds the typical well-scoped range of 3-15. Even for a broad supply chain platform, 50+ tools hits the rubric's 'extreme mismatch' threshold. The domain is comprehensive, but the sheer number overwhelms and likely complicates agent tool selection.
The tool surface covers the full lifecycle from project creation, BOM management, sourcing, quoting, planning, checkout handoff, orders, returns, issues, warranties, catalog updates, supplier profiles, and validation. It handles buyer and supplier sides with appropriate state transitions, and includes meta tools for connection and schema guidance. No obvious critical gaps exist.