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AiAgentKarl

shared-context-cache-mcp-server

confirm_entry

Confirm a cached result is accurate to increase its trust score. Collaborative verification by multiple agents enhances reliability for shared reuse.

Instructions

Confirm a cached result is accurate. Increases the entry's trust score.

When you use a cached result and verify it's correct, confirm it. This builds trust for other agents: entries confirmed by multiple agents are more reliable than unverified ones.

NETWORK EFFECT: More agents confirming = higher trust = more reuse.

Each agent can confirm an entry once. Duplicate confirmations are ignored.

Args: key: Cache key to confirm (e.g. 'weather:berlin:2026-03-28') agent_id: Your agent identifier (e.g. 'research-agent-v1')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
agent_idNomcp-agent

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral transparency. It discloses that each agent can confirm an entry once, duplicates are ignored, and trust scores increase. It does not cover potential side effects or failure modes, but the core behaviors are well explained.

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 well-structured: it starts with a clear primary action statement, then explains the benefit and behavior, and finally lists arguments with examples. Every sentence adds value without unnecessary fluff.

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 context includes an output schema, the description does not need to explain return values. It covers the tool's purpose, behavior, and parameters sufficiently for a simple confirmation action. The description is complete for its complexity.

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

Parameters5/5

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

Schema coverage is 0%, so the description must explain parameters. It does so effectively, providing a clear example for 'key' (e.g., 'weather:berlin:2026-03-28') and explaining that 'agent_id' defaults to 'mcp-agent'. This adds significant meaning beyond the bare schema.

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 that the tool confirms a cached result and increases trust score, with a specific verb ('confirm') and resource ('cached result'). It distinguishes itself from sibling tools like cache_store, cache_list, etc., by focusing on verification and trust building.

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 explains when to use the tool: 'when you use a cached result and verify it's correct, confirm it.' It also notes that duplicate confirmations are ignored and highlights the network effect. However, it does not explicitly state when not to use it or provide alternative tools for other scenarios.

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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