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fastmcp-me

Agent Knowledge MCP

by fastmcp-me

ask_mcp_advice

Describe your intended action and task to receive AI-filtered advice from the project's .knowledges directory.

Instructions

Advanced project guidance using AI-filtered knowledge from .knowledges directory

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intended_actionYesWhat you intend to do (e.g., 'implement feature', 'fix bug', 'deploy')
task_descriptionYesDetailed description of the specific task
scopeNoScope of guidance neededproject

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior1/5

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

No annotations are provided, and the description offers minimal behavioral disclosure. It does not explain what happens when invoked (e.g., reading files, calling external APIs), what the output format is, or any side effects. The agent has no insight into the tool's operation beyond the vague phrase 'AI-filtered knowledge'.

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 concise sentence with no extraneous content. It front-loads the core purpose, but could be slightly more informative without losing brevity.

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?

Despite the presence of an output schema (not shown), the description does not convey the nature of the guidance (e.g., textual advice, structured recommendations) or any limitations. As a guidance tool, more context about expected responses and scope of knowledge would be necessary for an agent to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already provides descriptions for all three parameters (intended_action, task_description, scope) with 100% coverage. The tool description adds no further parameter-level information, so it meets the baseline but does not enhance understanding.

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?

The description clearly states the tool provides 'Advanced project guidance' using AI-filtered knowledge from a specific directory, which indicates a consulting or advisory function. However, it does not explicitly distinguish from sibling tools like ask_user_advice, though the mention of 'AI-filtered' hints at automation vs. human input.

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?

There is no guidance on when to use this tool versus alternatives such as ask_user_advice. No prerequisites, exclusions, or context for invocation are mentioned, leaving the agent to infer usage from the tool's name and description alone.

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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