Skip to main content
Glama

backlog_remember

Record durable facts, procedures, or preferences for future sessions. Correct or replace existing knowledge using supersedes or state_key. Use for stable information worth remembering.

Instructions

Write a durable memory — a stable fact, a procedure, or a preference you should know next session. Use when you learn something worth keeping: "this repo deploys via wrangler", "Goga prefers terse evidence bullets". To CORRECT existing knowledge, pass supersedes (the old MEMO- id is expired, lineage kept) or state_key (previous holders of the same evolving fact are closed). Do not use for task events — completions are captured automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe memory body (markdown) — the fact itself.
titleYesMemory title (required, like a task title) — a short human-readable label for the fact. Title and body are both first-class.
layerNosemantic = stable fact (default). procedural = how-to/process. episodic = a specific event worth keeping.
contextNoScope container id (e.g. "FLDR-0001") — enables scoped recall and wakeup.
tagsNoFreeform labels for filterable recall.
entity_refsNoSource entities this knowledge derives from (e.g. ["TASK-0676"]).
kindNoTemporal kind: current fact / historical fact / future plan / preference / timeless (exempt from recency decay).
state_keyNoEvolving-fact key (e.g. "build.bundler"). Storing a new memory with an existing key closes the previous holder.
occurred_atNoWhen the remembered event occurred — ISO date/datetime. Decay uses this instead of write time.
valid_untilNoExpiry — ISO date/datetime. After this the memory drops out of recall.
supersedesNoMEMO- id this memory replaces. The predecessor is soft-expired.
derivedNoMark as inference (consolidator output). Requires non-empty entity_refs citing the sources.
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: writing immutable memories, correction via supersedes or state_key, scoping via context, and decay via kind (timeless exempts). It does not mention rate limits or exact side effects but covers essential behavioral traits.

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 (a single paragraph), front-loads the core purpose, and uses bold for emphasis. Every sentence adds value, with no wasted words. It is efficiently structured for quick understanding.

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

Completeness3/5

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

While the description covers main use cases and parameter semantics, it omits details about return values or error conditions. Given the tool's complexity (12 parameters, no output schema), a complete description would include what the tool returns, but it is still adequately helpful for selection and basic invocation.

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 100%, so baseline is 3. The description adds meaning beyond the schema by explaining correction mechanisms (supersedes, state_key) and temporal semantics (kind, decay). This additional context justifies a score of 4.

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 tool writes durable memories, including stable facts, procedures, or preferences. It distinguishes itself from siblings by noting it should not be used for task events (which are captured automatically), and explains how to correct existing knowledge, differentiating from update or delete operations.

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 when to use (when learning something worth keeping) and provides clear guidance on not using for task events. It also explains how to correct knowledge with supersedes or state_key. However, it does not explicitly name sibling tools as alternatives, leaving the guidance slightly implicit.

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/gkoreli/backlog-mcp'

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