Query persisted checkpoints across Algenta agent runs.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| run_id | No | ||
| status | No | ||
| request_hash | No | ||
| checkpoint_id | No | ||
| policy_snapshot_id | No | ||
| schema_snapshot_id | No |
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 must disclose behavioral traits. It only says 'Query persisted checkpoints' without mentioning read-only behavior, pagination, latency, or any side effects. This is insufficient for understanding the tool's behavior.
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 concise sentence with no fluff. It front-loads the verb and resource. However, given the tool's complexity (8 parameters), it may be overly brief.
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 8 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain what a checkpoint is, how to use filters, or what the response contains, leaving the agent with insufficient information.
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 0%, and the description does not explain any of the 8 parameters. Parameter names like 'run_id' and 'status' are somewhat indicative, but the description adds no meaning beyond the schema, failing to compensate for the lack of parameter descriptions.
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 'Query' and the resource 'persisted checkpoints across Algenta agent runs', indicating a query operation over multiple runs. However, it does not differentiate from the sibling tool 'get_agent_run_checkpoints', which may be more specific.
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?
No guidance is provided on when to use this tool versus alternatives like 'get_agent_run_checkpoints' or other query tools. There is no context on filtering, prerequisites, or scenarios where this tool is appropriate.
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.
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.
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.
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.
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.
