Full entity onboarding: creates initial RED assessments for all 39 checks, collects auto-evidence from live sources, re-assesses, and returns readiness score.
| Name | Required | Description | Default |
|---|---|---|---|
| entity_id | No | Entity ID to onboard |
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, the description carries the full burden. It discloses that the tool performs multiple mutating actions: creates initial RED assessments, collects auto-evidence from live sources, and re-assesses. It also states the return value (readiness score). However, it does not address idempotency, reversibility, or prerequisites.
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?
Single sentence with a colon-led summary and comma-separated steps. It is front-loaded and contains no filler, making it easy to parse quickly.
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 tool with one parameter, full schema coverage, no output schema, and no annotations, the description covers the main behavior and output. It lacks details on prerequisites or failure modes, but is adequate for the tool's simplicity.
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?
Input schema already documents the entity_id parameter with 100% coverage. The description does not add extra meaning about the parameter beyond referencing the entity, so baseline 3 applies.
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 opens with 'Full entity onboarding' and specifies the exact sequence: creates initial RED assessments for all 39 checks, collects auto-evidence, re-assesses, and returns readiness score. This clearly differentiates it from siblings like assess_all or readiness_check by describing a comprehensive onboarding workflow.
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 this is the tool for onboarding a new entity, but it does not explicitly state when to use it over alternatives like assess_all or create_entity. No exclusions or alternative tool mentions are provided.
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.