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vbcherepanov

total-agent-memory

memory_recall

Read-onlyIdempotent

Search past sessions for decisions, solutions, facts, and lessons before starting a new task.

Instructions

Search ALL memory: decisions, solutions, facts, lessons from ALL past sessions. 6-stage pipeline: FTS5+BM25 → semantic → fuzzy → graph → (optional) CrossEncoder → (optional) MMR. Default: hybrid mode (BM25 + semantic + RRF). Use BEFORE starting any task. v11.0: routes to fast hot path when MEMORY_MODE=fast (default). Use memory_search_fast / memory_explain_search for explicit fast routing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoProgressive-disclosure mode: 'search' (default) = normal results, 'index' = ultra-compact metadata only (id+title+score+type+project+created_at, ~40-60 tok/hit, no cognitive expansion, use memory_get(ids=...) to fetch full content), 'timeline' = top-K hits expanded with ±neighbors from same session (chronological)search
typeNoall
limitNo
queryYesWhat to search for
branchNoFilter by git branch (also includes branch-agnostic records)
detailNoLevel of detail: 'compact' ~50 tokens/result (id+title+score), 'summary' truncates content to 150 chars, 'full' returns everything, 'auto' picks based on query complexity (paths/urls/code → full, short → compact). Ignored when mode!='search'.full
fusionNoScore fusion method: 'rrf' = Reciprocal Rank Fusion (better multi-tier ranking), 'legacy' = original additive scoringrrf
intentNoFilter by classified intent (question|procedural|fact|decision|problem|solution|incident|plan)
rerankNoEnable CrossEncoder re-ranking for higher precision (adds ~30ms latency)
topicsNoFilter results to records tagged with any of these topics (from deep enrichment)
diverseNoEnable MMR diversity to reduce redundant results (useful for broad queries)
projectNoFilter by project name
entitiesNoFilter by extracted entity names (technology/person/project, case-insensitive)
neighborsNoTimeline mode only: how many records before/after each hit to include.
expand_budgetNoMax number of additional records to include via graph expansion
decisions_onlyNoReturn only structured decisions (v8.0): type=decision AND tags contain 'structured'. Results include parsed schema payload under 'decision'.
expand_contextNoAdd graph-related records (1-hop neighbors via knowledge graph) as 'expansion' results

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description discloses behavioral details such as the 6-stage pipeline, default hybrid mode, latency implications of rerank, and the behavior of timeline mode (top-K hits expanded with neighbors). This provides rich transparency about how the tool operates.

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 (5 sentences) and front-loaded with the core purpose, followed by pipeline overview, defaults, and usage guidance. Every sentence adds value with no 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?

Given the tool's complexity (17 parameters, many with detailed schema descriptions) and no output schema, the description is complete enough. It provides an overview, pipeline context, default behaviors, and usage guidance, covering all necessary context for invocation.

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 88%, already high. The tool description adds little beyond the schema's parameter descriptions; it does mention defaults and pipeline stages but does not elaborate on parameter semantics beyond what the schema provides. Baseline of 3 is appropriate.

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's purpose: 'Search ALL memory: decisions, solutions, facts, lessons from ALL past sessions.' It also distinguishes itself from memory_search_fast by noting explicit fast routing, making the purpose and differentiation unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit usage guidance: 'Use BEFORE starting any task' and directs users to memory_search_fast / memory_explain_search for explicit fast routing. This clearly tells when to use this tool versus alternatives.

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

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