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ai-netcafe

by com.ainetcafe
OverviewDiscussionsAdmin

Recall stored memories

recall
Read-onlyIdempotent

Retrieve previously stored memories, optionally filtered by search query and/or project. Call at the start of work on a known project to restore context: why decisions were made, known fixes, preferences. Example — GET https://ainetcafe.com/t/recall?query=<what+to+remember> (needs a workspace/key for durable memory)

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": "recall"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax results (default 8, up to 20).
queryNoOptional search terms; omit to list the most recent.
projectNoOptional project filter.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover read-only and non-destructive behavior. The description adds a prerequisite (needs a workspace/key for durable memory) and explains the type of context it retrieves (decisions, fixes, preferences). The example GET request also illustrates the call style. No contradiction with annotations.

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 concise and front-loaded with the core purpose. It includes an example and a key prerequisite in two sentences, with no redundant information. Every sentence serves a purpose.

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

Completeness5/5

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

The description covers the tool's purpose, when to use it, a usage example, and an authentication prerequisite. With full parameter documentation, an output schema, and annotations, the description is sufficiently complete. It also positions the tool well relative to its siblings.

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 provides detailed descriptions for all three parameters (limit, query, project), so the description adds little beyond restating that filtering is optional and showing an example that uses 'query.' With 100% schema coverage, the baseline is 3, and the description does not significantly enrich parameter meaning.

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 opens with 'Retrieve previously stored memories,' a specific verb and resource. It also specifies optional filtering by search query and project, and gives a concrete use case (restoring context at the start of work). This clearly distinguishes it from sibling tools 'remember' and 'forget.'

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 explicitly says to call it 'at the start of work on a known project' to restore context, which is clear when-to-use guidance. It does not explicitly name alternatives, but the phrasing and sibling names imply that 'remember' is for storing and 'forget' for deleting. The example and note about needing a workspace/key add practical context.

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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