Skip to main content
Glama
fitz2882

learned-experience

by fitz2882

Export or import the catalogue

transfer
Idempotent

Export or import learned experiences as JSONL to move them between models or tools. Import merges idempotently with newer records winning; embeddings are recomputed by the destination model.

Instructions

Portability. mode='export' writes every record as JSONL (to path if given, else returned inline). mode='import' reads JSONL from path or jsonl and merges it idempotently: newer wins on id clash, duplicates are merged. Paths are .jsonl files inside the transfer directory (relative names are resolved there). Embeddings are not transferred; they are recomputed by whichever model the destination uses.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
pathNoFile name or path (.jsonl) inside the transfer directory
jsonlNoInline JSONL for import
Install Server

TDQS

A4.7/5.0
Behavior5/5

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

The description goes well beyond the annotations, detailing the JSONL format, path resolution rules, idempotent merge behavior, conflict resolution (newer wins, duplicates merged), and the important caveat that embeddings are not transferred and are recomputed. This gives the agent substantial behavioral transparency beyond the simple readOnly/destructive/idempotent hints.

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 compact and front-loaded: the single word 'Portability' establishes intent immediately, followed by three dense, purposeful sentences covering modes, path behavior, merge semantics, and embedding caveats. No filler or redundancy.

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?

For a tool with no output schema and moderate parameter count, the description covers all necessary operational details: mode selection, input/output destinations, idempotency, conflict handling, and the embedding recomputation caveat. An agent has enough information to call the tool correctly and predict its side effects.

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

Parameters4/5

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

Schema coverage is 67%, with path and jsonl already described in the schema. The description adds significant semantic value by explaining the mode enum values in context, clarifying how path is resolved relative to the transfer directory, and defining idempotent merge semantics for import. This meaningfully supplements the schema.

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 states a clear verb-resource pairing: export or import the catalogue, with specific modes for each direction. The opening 'Portability' frames it as a bulk data movement operation, which distinguishes it from the sibling memory operations like record, recall, or 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 clearly explains when to use export vs import and how each mode behaves. It does not explicitly name alternatives or say 'use this instead of X', but the portability framing combined with the detailed mode semantics gives a clear context for choosing this tool over per-record siblings.

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

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/fitz2882/learned-experience'

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