Skip to main content
Glama

feedback_add_analysis

Set up a feedback analysis pipeline in a project directory to process user feedback automatically. Supply the directory path to generate the pipeline and extract insights.

Instructions

Generate feedback analysis pipeline (Pro feature)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
directoryYesProject directory
Behavior2/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It only says a pipeline will be generated and that the feature is Pro-gated; it does not state whether files are written, the directory is modified, authentication is required, or what side effects occur.

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 short sentence with no filler or repetition. The core action and the Pro-feature note are front-loaded. It is concise, though it sacrifices useful detail for 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?

With no annotations, no output schema, and minimal parameter descriptions, this description is not self-sufficient for invocation. An agent can infer the project directory from the schema but cannot tell what 'analysis pipeline' concretely involves, whether api_key must be supplied, or what success/return looks like. For a tool with only two parameters this is still under-specified.

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

Parameters2/5

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

Schema coverage is 50%: only 'directory' has a description. The tool description adds no parameter-level meaning, and 'api_key' remains entirely unexplained. Since the description does not compensate for the missing parameter context, an agent is left guessing about the api_key's role and whether it is required in practice.

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 states a clear action ('Generate') and a specific deliverable ('feedback analysis pipeline'), so an agent can grasp the tool's function. It is reasonably distinguishable from siblings like feedback_generate_system and feedback_add_widgets, though it does not explicitly contrast itself with them.

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 is provided on when to use this tool instead of related feedback tools. The phrase 'Pro feature' hints at a licensing prerequisite, but there is no mention of whether this should be used after feedback_generate_system, what project state is expected, or when an alternative is preferable.

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/barnburner121/claude-plugin-marketplace'

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