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Cachly — AI Cognitive Brain

Cachly — AI Cognitive Brain

by cachly-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

cache_stream_set

Store ordered string chunks, such as LLM token streams, into a Redis-backed cache for later retrieval and replay via a matching get tool.

Instructions

Cache a list of string chunks (e.g. LLM token stream) via Redis RPUSH. Each chunk is stored as a separate list element under cachly:stream:{key}. Replay with cache_stream_get.

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": {
      "instance_id": "<instance_id>",
      "key": "<key>",
      "chunks": "<chunks>"
    },
    "name": "cache_stream_set"
  }
}

Input Schema

NameRequiredDescriptionDefault
keyYesCache key
ttlNoTTL in seconds for the stored list (optional)
chunksYesOrdered list of string chunks
instance_idYesUUID of the cache instance

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description bears full burden. It reveals the Redis RPUSH operation and optional TTL, but does not clarify whether multiple calls append or overwrite, or discuss failure modes. Adequate but leaves some uncertainty.

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?

Two sentences covering purpose, storage, and companion tool. No redundant words. Highly efficient.

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?

Given the simple append-to-list operation, the description covers purpose, storage, and optional TTL. It does not specify return value, but that is minor. Contextually adequate.

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% with property descriptions. The description adds context beyond schema by explaining storage under cachly:stream:{key} and the pairing with cache_stream_get. It does not add new parameter details but enhances understanding.

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 caches a list of string chunks via Redis RPUSH, provides the storage pattern, and mentions the sibling cache_stream_get for replay. It distinguishes from other cache tools by specifying the list data structure.

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 gives a concrete use case (LLM token stream) and implies the tool is for appending to a list. It does not explicitly state when not to use it, but the sibling context helps. Minimal but sufficient guidance.

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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