Skip to main content
Glama

validate_component_logging

Checks that each component method logs output with a BaseModel and flags defensive dict-access antipattern self.params.get.

Instructions

AST-check that each component's required method calls the matching self.log_<component>_output(...) with a BaseModel instance (not a dict, not a wrong schema).

    Also flags ``self.params.get(...)`` anywhere in the file (PRM-004 —
    defensive dict-access antipattern on the params container).

    Returns ``{"any_errors": bool, "findings": [...]}``.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
strategy_dirYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries full burden but only mentions it is an AST check and returns findings. It does not disclose error handling, dependencies, or limitations, though the core behavior is adequately described.

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 relatively concise and front-loaded with the main purpose. However, the triple-quoted string formatting may obscure readability slightly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Considering no output schema, no annotations, and 0% schema coverage, the description is the sole source. It explains checks and return format but lacks parameter clarity, making it somewhat incomplete for an agent.

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 has one parameter (strategy_dir) with 0% description coverage, and the tool description does not explain its meaning or usage. The agent has no help understanding what value to provide.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is an AST-check for component logging, specifying it verifies required method calls with BaseModel and flags self.params.get() antipattern. It distinguishes from sibling tools by its specific focus on logging validation.

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 explicit guidance on when to use this tool versus other similar validation tools (e.g., validate_component_integration). The description does not provide context on prerequisites or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DolphinQuant/echolon'

If you have feedback or need assistance with the MCP directory API, please join our Discord server