update_execution_policy
Update one or more execution-policy thresholds for the active organization.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| risk_floor | No | ||
| min_confidence | No | ||
| allow_reexecution | No | ||
| require_calibration | No |
Algenta MCP Server
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
C2.6/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states that thresholds are updated, but does not mention permissions, immediate effect, idempotency, or whether the update overwrites or merges existing values.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, but its brevity comes at the cost of missing critical details. It earns a 4 for conciseness, not for completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no output schema, and no annotations, the description is insufficient. It does not explain inter-parameter dependencies, valid value ranges beyond schema, or the overall effect on the execution policy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description provides no information about any of the four parameters (risk_floor, min_confidence, allow_reexecution, require_calibration). The agent has no hint about their meaning beyond schema constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Purpose is clear: update execution-policy thresholds for the active organization. It specifies the verb 'update' and the resource 'execution-policy thresholds', but note that the schema includes boolean parameters (allow_reexecution, require_calibration) which are not strictly thresholds, causing a slight mismatch.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like get_execution_policy or list_execution_policy_snapshots. The description does not provide exclusions, prerequisites, or scenarios for this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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TDQS
C2.7/5.0
Disambiguation4/5
Most tools target distinct resources or actions, but there is some overlap (e.g., run_repository_fix vs run_repository_pipeline vs simulate_repository) that could cause confusion. Overall, descriptions help differentiate.
Naming Consistency3/5
Tool names are primarily snake_case with a verb_noun pattern, but there are inconsistencies (e.g., single-word verbs like 'simulate', 'tokenize', and mixed prefixes like 'preview_', 'product_'). The pattern is readable but not uniform.
Tool Count1/5
With 140 tools, the server is extremely over-scoped for typical MCP usage. This overwhelms agents and suggests poor separation of concerns, likely violating the principle of minimal tool surfaces.
Completeness4/5
The tool set covers a wide range of functionalities including data onboarding, simulation, decisions, repository management, and admin operations. Minor gaps exist (e.g., no update_agent_run), but core workflows are well-supported.