celiums-memory

research_project_list

List research projects for any user, including counts of findings and open gaps. Quickly identify ongoing investigations to avoid duplication and track progress.

Instructions

List all research projects for a user, with counts of findings and open gaps. Use to discover what investigations are already in progress.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "research_project_list"
  }
}

Input Schema

Name	Required	Description	Default
`userId`	No

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.2.5Apr 28, 2026

TDQS

A3.8/5.0

Behavior2/5

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

No annotations are provided, so the description must cover behavioral traits. It mentions 'list all research projects for a user' but does not disclose whether it requires authentication, is read-only, supports pagination, or what happens when the optional 'userId' is omitted. This is insufficient for safe invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no fluff. The first sentence states the core action and output, and the second provides usage guidance. It is appropriately front-loaded and efficient.

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

Completeness4/5

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

Given the tool has no output schema, the description provides a reasonable outline of the return data (list of projects with counts). It covers the essential context for a list operation, though it could mention whether results are paginated or ordered. Overall, it is largely complete for the tool's simplicity.

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 schema has one optional parameter 'userId' with 0% description coverage. The description adds meaning by stating it retrieves projects 'for a user,' implying a filter. However, it does not specify that omitting userId likely defaults to the current user, nor does it clarify if this is a required filter for explicit user queries.

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 the tool lists all research projects for a user, including counts of findings and open gaps. It distinguishes from sibling tools like 'research_project_create' (create) and 'research_finding_add' (add finding) by specifying the output and purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'Use to discover what investigations are already in progress,' which provides clear context for when to use the tool. While it does not explicitly list when not to use or mention alternatives, the guidance is sufficient for an AI agent to infer appropriate usage.

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