Upload contract text for DORA Art. 30 analysis. Creates document record with SHA-256 hash, version tracking, audit trail.
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | No | Entity ID | |
| file_name | No | Original file name | |
| contract_text | No | Contract text (extracted from PDF) | |
| document_type | No | ict_outsourcing_agreement | dpa | sla | master_service_agreement | |
| provider_name | No | Provider name |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden of behavioral disclosure. It does disclose important behaviors: creating a document record with a SHA-256 hash, version tracking, and an audit trail. However, it does not mention prerequisites (e.g., entity must exist), potential side effects (e.g., overwrite behavior), or authentication/authorization needs, leaving significant 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 extremely concise and well-structured: two sentences that first state the primary action and then detail the resulting record traits. Every word adds value, with no fluff or redundancy.
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's complexity (5 parameters, no output schema, no annotations), the description is incomplete. It does not explain the return value or next steps after upload (e.g., whether an ID is returned, or that the document can be analyzed with contract_analyze). Since there is no output schema, the description should have compensated by outlining expected outcomes.
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 input schema has 100% parameter description coverage, so the baseline is 3. The description adds no additional parameter-level meaning beyond what the schema already provides; it does not explain relationships between parameters or clarify unusual aspects (e.g., all parameters are optional despite upload requiring some context).
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 specific action (upload contract text), the resource (contract text for DORA Art. 30 analysis), and the resulting side effects (creates document record with SHA-256 hash, version tracking, audit trail). This distinguishes it from sibling tools like contract_analyze or contract_status, which have different purposes.
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 provides clear context by specifying that the upload is for DORA Art. 30 analysis, implying this tool is for ingesting new contracts rather than analyzing or checking existing ones. However, it does not explicitly mention when not to use it or name alternative tools, so it stops short of full guidance.
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.
Several tools overlap in purpose, particularly contract analysis (check_contract, contract_analyze, llm_clause_check) which could confuse agents. Assessment-related tools (readiness_check, assess_all, article_status) also have partially overlapping functionality. However, most tools have distinct resources and actions with detailed descriptions.
Tool names are consistently snake_case and mostly follow a verb_noun pattern (e.g., create_entity, generate_report, register_provider). Minor deviations like contract_analyze and llm_clause_check invert the verb-noun order, but the overall pattern is predictable.
50 tools is a very large surface for a single server, exceeding the threshold for 'too many' tools. While the DORA domain is broad, this breadth makes it challenging for agents to navigate and select the right tool efficiently.
The tool set covers the full DORA compliance lifecycle: entity onboarding, contract analysis, provider management, assessments, evidence, reporting, and incident workflows. Simulation and cross-regulation tools add depth. Minor missing CRUD operations (e.g., update/delete entity) but agents can work around.