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Glama

note

Save durable facts, decisions, or findings to long-term memory for retrieval by relevance across sessions. Preserve context agents need later.

Instructions

Save a general long-term memory (fact, decision, finding). Stored as type='note'.

Timeless knowledge -- retrieved by relevance, not recency. Bring it back with recall() (or search(type='note')); pulse() also shows the few most recent ones as warm-up breadcrumbs.

title: one line naming what this memory is about, in the words someone would look for it by. It is what a list shows instead of the opening of the body, and it outweighs every other field in search, so a title that repeats the type ("note about the parser") names nothing. At most 120 characters, and a name that needs more than that is summarizing the body instead of naming it.

content: ONE fact, and what a reader needs to use it -- what holds, where it holds, what it rules out. Retrieval ranks whole memories, so a body answering four questions comes back for all four and is read for one: write the second subject as its own memory, on its own domain, and connect the two with link_memories(). A [[uid]] typed inside a body is a reference a reader can follow, not an edge -- get_relations() and the graph do not see it until link_memories() creates one. Past a couple of thousand characters, a body is usually several memories written as one.

domain: the subject this belongs to, as a path from the outermost scope in ('acme/x100/p200'). File it as deep as the fact is specific -- a note about one routine goes on the routine, and still comes back when someone asks about the module or the product above it.

also: other domain paths this belongs to, comma-separated. domain is where the memory LIVES -- one path, one parent chain. also is for the subjects that cut ACROSS that tree: the same routine belongs to the module it runs in and to the end-to-end flow it is one step of, and neither of those is the other's ancestor. Every read scoped to any of those paths returns it. A path that domain already sits under is dropped as redundant -- the result echoes what was stored.

tags: comma-separated keywords and synonyms. Retrieval is BM25 over content, tags and domain paths, and tags weigh second only to the body, so they are where a memory becomes findable by words its own text never uses -- the identifier, the symbol, the error string, the plain-language phrasing someone will actually type. A memory with none is reachable only by quoting itself.

review_after: when this stops being safe to trust unchecked, as a date ('2026-11-01') or a span from today ('90d'). pulse() counts what is overdue in a scope as scope.stale and optimize_scan lists it. Leave it empty for anything that does not go stale -- most facts do not, and a date nobody meant is worse than none.

source_ref: what the fact came FROM -- a path, a URL, a table name -- so a later pass can check the claim against the thing itself instead of inferring what to check from the wording.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
alsoNo
tagsNo
titleYes
domainNo
contentYes
sessionNo
source_refNo
review_afterNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.1.1
    • addedInput schema / properties / also
      Added value: +{
      +  "default": "",
      +  "title": "Also",
      +  "type": "string"
      +}
    • addedInput schema / properties / review_after
      Added value: +{
      +  "default": "",
      +  "title": "Review After",
      +  "type": "string"
      +}
    • addedInput schema / properties / source_ref
      Added value: +{
      +  "default": "",
      +  "title": "Source Ref",
      +  "type": "string"
      +}
    • addedInput schema / properties / title
      Added value: +{
      +  "title": "Title",
      +  "type": "string"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "content"
      -]New value: +[
      +  "title",
      +  "content"
      +]
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and discloses real behavior: input weighting in BM25 (title outweighs all, tags second to body), redundant domain paths being dropped and echoed back, [[uid]] not creating graph edges until link_memories(), review_after surfacing as scope.stale in pulse()/optimize_scan, and length warnings. This is well beyond a bare field list.

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

Conciseness4/5

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

Front-loaded purpose sentence, then header-per-parameter structure, which is appropriate given 0% schema coverage. The length is largely earned, though a few editorial asides ("warm-up breadcrumbs") could be trimmed.

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?

For an 8-param, no-annotation, no-output-schema tool, the description is nearly complete: storage semantics, retrieval behavior, and all params but `session` are covered. Return values need not be explained absent an output schema, but the undocumented session param leaves a small gap.

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 description coverage is 0%, so the description must compensate, and it richly documents 7 of 8 params (title, content, domain, also, tags, review_after, source_ref) with formats and examples. The `session` parameter is entirely unmentioned, leaving one gap in an otherwise strong effort.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Save a general long-term memory") and clarifies the stored type (type='note'), and routes retrieval to recall()/search()/pulse(). It implies differentiation from specialized save siblings (checkpoint, handoff, anti_pattern) via the word "general," but never names those siblings explicitly to draw the boundary.

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?

Gives clear when-to-use context ("Timeless knowledge -- retrieved by relevance, not recency") and names the retrieval alternatives. However it offers no explicit when-NOT-to-use guidance and does not route between this and the other write-time siblings (checkpoint, handoff, reasoning), leaving that selection to inference.

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