article_status
Detailed Ampel for a specific DORA article. Each check with GREEN/YELLOW/RED conditions and evidence.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| article | No | e.g. Art. 28 | |
| entity_id | No | Entity ID |
Detailed Ampel for a specific DORA article. Each check with GREEN/YELLOW/RED conditions and evidence.
| Name | Required | Description | Default |
|---|---|---|---|
| article | No | e.g. Art. 28 | |
| entity_id | No | Entity ID |
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 provided, the description carries the burden of disclosing behavior. It does explain that the tool returns status conditions (GREEN/YELLOW/RED) and evidence, which gives some insight into output. However, it does not explicitly state that it is a read-only operation, whether it queries live data, or any side effects or error conditions.
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 states the core purpose ('Detailed Ampel') and key features (conditions with evidence). It is concise and free of fluff, though a slightly more structured breakdown could improve scannability.
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 no output schema and no annotations, the description should more fully explain what the returned report contains and any usage context. It mentions evidence and conditions but does not clarify the number of checks, how evidence is presented, or whether the tool computes results on demand. It is minimally complete for a simple status tool but leaves gaps for an agent deciding to invoke it.
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 100%, so the parameters 'article' and 'entity_id' are already documented. The description does not add additional meaning beyond confirming the tool is for a specific DORA article, which aligns with the 'article' parameter. Per rubric, baseline 3 is appropriate when schema covers all parameters.
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 identifies the tool as providing a detailed traffic-light status ('Ampel') for a specific DORA article, with conditions and evidence. It distinguishes itself from broad assessments like 'assess_all' by specifying it is for a single article, but it does not explicitly name alternatives or contrast with sibling 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 does not provide any guidance on when to use this tool versus alternatives. It simply describes the output without indicating prerequisites, exclusions, or preferred contexts. No mention of when to choose 'article_status' over 'evidence_summary' or 'gap_report'.
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.