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Glama

Recall Memory

faf_recall
Read-onlyIdempotent

Retrieve project memories ranked by priority and recency, filtered by query, tags, or type. Surfaces past decisions from the project soul for read-only recall.

Instructions

Recall memories from the project soul (soul.fafm), ranked by priority then recency, filtered by query/tags/type. Returns the matching entries. Reads only. Use it to surface past decisions; faf_etch adds new ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoProject path. Sets session context for subsequent calls.
tagsNoFilter by tag intersection
typeNoFilter by memory type
limitNoMax memories to return
queryNoCase-insensitive substring match on memory text (optional)
minPriorityNoPriority floor (default ephemeral)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
soulNo
totalYesNumber returned
memoriesYes
soulTotalNoTotal memories in the soul

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv5.9.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false and destructiveHint=false, so 'Reads only' is largely redundant. However, the description adds real behavioral context beyond the annotations: the backing store (soul.fafm), the deterministic ranking order (priority then recency), and the fact that filtering is conjunctive across query/tags/type.

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?

Three short sentences, front-loaded with the core action and scope, then filters, then the routing hint to faf_etch. No filler; every clause carries information.

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?

With an output schema present, the description need not explain return shape, and the one-line 'Returns the matching entries' is sufficient. For a six-parameter read tool it covers filters, ordering, and the sibling write path, though it omits default limit behavior and any note on empty results.

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 the schema already documents all six parameters, including the query substring semantics and the minPriority default. The description only restates the filter dimensions and adds result ordering (priority then recency), which is genuinely extra but marginal against a fully documented schema. Baseline 3 applies.

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?

States a specific verb and resource ('Recall memories from the project soul (soul.fafm)') and immediately specifies the retrieval model ('ranked by priority then recency, filtered by query/tags/type'). It explicitly names the sibling it is not ('faf_etch adds new ones'), so an agent can route between the read and write tools without opening either schema.

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 a concrete use case ('surface past decisions') and names the complementary alternative, faf_etch, with its contrasting behavior. It stops short of stating when NOT to use it (e.g. when to prefer faf_context or a live search over stored memories), so it is clear context without explicit exclusions.

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