get_security_scoreGet the active project's security score (0–100) and the count of open findings by severity. Pass trendDays to also get the daily score history over that many days — that is how you tell whether a project is improving or drifting. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
| trendDays | No | Days of score history to include, 1-365. Omit for the current score only. |
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?
The annotation readOnlyHint=true already indicates this is a read operation. The description adds behavioral context by noting that the tool depends on the active project context, which is not stated in the schema. No side effects or destructive actions are implied, and nothing contradicts the annotation.
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 two sentences, direct, and free of unnecessary details. It packs essential information about the return value, the optional parameter, and the context requirement without verbosity.
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?
There is no output schema, but the description clearly states the tool returns a score, a count of findings by severity, and optionally a history. This provides sufficient context for an agent to understand the tool's output. The missing formal output structure is acceptable given the clarity of the prose.
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 single parameter trendDays is fully described in the schema (range 1-365, nullable, default null). The tool description reinforces its purpose and effect (including history vs current-only). Since the schema already provides strong coverage, the description adds marginal but useful clarification.
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 'Get' and the resource 'security score', and explicitly lists what is returned: the score (0–100), count of open findings by severity, and optionally the daily score history. It also distinguishes from related tools like get_governance_score and get_security_findings by focusing on the security score and its trend.
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 explains when to use the trendDays parameter ('to get the daily score history... that is how you tell whether a project is improving or drifting') and notes the current score is returned when omitted. It also mentions 'Requires project context', implying the need for an active project. It does not explicitly contrast with sibling tools, but the purpose is clear enough.
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.
The tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.
All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.
With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.
The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.