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ctx-memory

ctx-memory

by parth0072
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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save_handoff

Preserves a where-we-left-off summary—goal, decisions, current state, and next steps—so the next AI session can resume work with shared context.

Instructions

Save a where-we-left-off summary for the next AI.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "summary": "<summary>"
    },
    "name": "save_handoff"
  }
}

Input Schema

NameRequiredDescriptionDefault
projectNoglobal
summaryYesgoal, decisions, current state, next steps
from_modelNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior2/5

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

With no annotations at all, the description carries the full burden of behavioral disclosure, and it says nothing about whether saving overwrites a prior handoff for the same project, whether writes are persistent, or what permissions are needed. For a mutation tool with zero annotation coverage this is a meaningful gap.

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?

A single tight sentence with the action front-loaded and no filler; every word earns its place.

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

Completeness2/5

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

For a 3-parameter write tool with no annotations and no output schema, the description is too thin: it omits the project scoping behavior, the meaning of the optional parameters, and any indication of what happens on repeat saves.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33% (only 'summary' is documented), and the description mentions no parameters at all. It does not explain the 'project' grouping key or what 'from_model' is for, so it fails to compensate for the coverage gap.

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 clear verb+resource: 'Save a where-we-left-off summary'. The phrase 'for the next AI' makes the intent concrete and separates it from the storage/retrieval siblings (remember, recall). It does not explicitly contrast with the closest sibling, remember, so it stops short of a 5.

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

Usage Guidelines3/5

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

'for the next AI' implies the trigger is an end-of-session handoff, giving implied usage context. However, it never says when to prefer this over remember, nor when not to use it, leaving the agent to infer the distinction.

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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