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Glama
M-T-D-N

agentmemory-codex-windows

memory_timeline

Retrieve a chronological observation window around an ISO timestamp or keyword to reconstruct nearby activity, then page through results using before, after, and offset.

Instructions

Retrieve a chronological observation window around an ISO timestamp or keyword to reconstruct nearby activity. before and after define the full window; follow nextOffset with offset until null. Returns observations and pagination metadata, bounded to 100 entries and 2 MiB per page. Omitted project searches all projects; specify an exact project to narrow it. Records retention access unless trackAccess=false. Use memory_smart_search for relevance-ranked discovery.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNoFull-window observations after anchor (default 5; zero is valid)
anchorYesAnchor point: ISO date or keyword
beforeNoFull-window observations before anchor (default 5; zero is valid)
offsetNoOffset within the full window (default 0); continue at nextOffset until null
agentIdNoOptional agent ID; omit for configured scope, or use '*' for a deliberate cross-agent read
projectNoExact project path; use '*' for all projects. Omission keeps the existing all-project scope.
trackAccessNoSet to false for analytical reads that must not reinforce access-based retention (default true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0-preview.14-glama.1

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses pagination mechanics (follow nextOffset with offset until null), hard bounds (100 entries, 2 MiB per page), project scoping defaults, and a retention side effect ('Records retention access unless trackAccess=false'). It doesn't describe the observation record shape or error/empty behavior, keeping it below a 5.

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-loads the purpose in the first sentence, then layers window/pagination, scoping, retention, and the sibling pointer. Dense and largely waste-free, though a sentence or two overlaps with what the schema already documents.

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, so the description must explain returns, and it does ('Returns observations and pagination metadata') along with pagination bounds and scoping behavior. Covers what an agent needs to call it correctly, with only minor gaps around record contents.

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 the baseline is 3, but the description adds real meaning beyond the schema: the relationship of before/after as the 'full window', the offset/nextOffset continuation loop, and the semantics of omitting project (search all) and trackAccess=false (non-retention analytical reads).

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 ('Retrieve') and resource ('chronological observation window around an ISO timestamp or keyword') with the goal ('reconstruct nearby activity'). It also differentiates from the relevance-ranked sibling by explicitly naming memory_smart_search, so an agent can route 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 clear context: this tool is for chronological/temporal reconstruction, and explicitly names memory_smart_search as the alternative for relevance-ranked discovery. It stops short of enumerating when-not conditions or edge cases, but the primary routing decision is spelled out.

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