Skip to main content
Glama
wanbnn
by wanbnn

recall_project

Retrieve past research, delivery summaries, and reviews for a project to inform current UI decisions.

Instructions

Recall prior research, delivery summaries, and reviews for a project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNo
limitNo
project_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only says 'recall' without detailing return format, sorting, filtering, authentication needs, or what kind of summaries are included. This is a minimal disclosure that leaves agents uncertain about operational behavior.

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 a single, front-loaded sentence with no fluff. It efficiently communicates the core purpose, using only seven words while still distinguishing the tool's function.

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?

Although an output schema exists, the description does not explain how the kind or limit parameters affect results, what types of 'prior research' or 'reviews' are included, or how to filter by project. For a retrieval tool with three parameters, this is too incomplete for reliable selection and invocation.

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 description coverage is 0%, and the description does not mention any of the three parameters (project_id, kind, limit). The agent receives no guidance on how to set or interpret these parameters beyond the schema's basic types and constraints, so the description fails to compensate for the coverage gap.

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 uses a specific verb ('recall') and names the resource type ('prior research, delivery summaries, and reviews for a project'), clearly distinguishing it from sibling tools like research_niche (which creates research) and remember_delivery (which stores delivery info). This gives the agent a precise idea of what the tool does.

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

Usage Guidelines3/5

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

The description implies usage for retrieving historical project information but does not explicitly state when to use this tool versus alternatives like inspect_reference or review_implementation. It lacks explicit exclusions or alternative tool references, so guidance is only implied.

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/wanbnn/MCPUIResearch'

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