Skip to main content
Glama

td_memory_save

Save structured, replayable techniques to a project or global library for reuse in TouchDesigner networks.

Instructions

Save a structured, replayable technique to the project or global library.

Use the output of td_memory_learn as the technique input, or construct a technique dict manually. Prefer td_knowledge_save when you want to capture free-form markdown prose/notes rather than a replayable network recipe.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoOverride technique name.
tagsNoAdditional tags.
notesNoFreeform notes about this technique.
scopeNo'project' or 'global'.project
techniqueYesTechnique dict (from td_memory_learn output).
descriptionNoOverride description.
Behavior3/5

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

Annotations indicate write operation with destructiveHint=false. Description adds context about saving to project/global library and input format, but does not disclose overwrite behavior, idempotency, or error conditions beyond what annotations already convey.

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?

Two sentences with no wasted words. First sentence states purpose, second provides usage guidance and alternative. 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?

No output schema exists, but description covers input sources, scope options, and alternative tool. Could mention return value on success, but given the tool's simplicity, it is reasonably complete.

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?

Schema description coverage is 100%, so baseline is 3. The description adds minimal extra meaning for parameters, only noting that technique can be from td_memory_learn or manual construction, which is useful but not significant beyond 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 clearly states the verb 'Save' and resource 'structured, replayable technique'. It distinguishes from sibling tool td_knowledge_save for free-form notes, and mentions using output from td_memory_learn as input.

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?

Explicitly says when to use this tool vs td_knowledge_save, and that technique input can come from td_memory_learn. Lacks exclusions for other sibling tools like list or recall, but guidance is clear.

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/dreamrec/TDPilot'

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