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AiAgentKarl

shared-context-cache-mcp-server

cache_lookup

Look up cached results by key to avoid redundant computation. Returns the stored value with a trust score indicating verification level.

Instructions

Look up a cached result by key. Returns the stored value if found, with trust score.

Use this BEFORE computing expensive results -- another agent may have already computed and cached the answer, saving tokens and latency.

Higher trust_score = more agents have verified this result is accurate.

Args: key: Cache key (e.g. 'weather:berlin:2026-03-28', 'research:quantum-computing') agent_id: Your agent identifier for analytics tracking

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYes
agent_idNomcp-agent

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states it returns a value with a trust score and explains the trust_score meaning. However, it does not describe behavior when the key is not found (e.g., returns null or error). This is a minor gap for a lookup tool.

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 and concise: a short intro sentence, followed by usage guidance, trust score elaboration, and parameter docs with examples. No extraneous information, and front-loaded with the core purpose.

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 tool's simplicity (2 parameters, lookup only), the description covers input, usage context, and return value aspects. It distinguishes from siblings. However, it could mention the outcome when the key is missing, and the output schema exists but is not referenced. Still, it is largely complete.

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 description coverage is 0%, but the description fully compensates by explaining both parameters: 'key' with example patterns like 'weather:berlin:2026-03-28', and 'agent_id' as an analytics identifier. This adds significant meaning beyond the schema's type and title.

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 action: 'Look up a cached result by key. Returns the stored value if found, with trust score.' It specifies the resource (cache) and the verb (look up), and differentiates from sibling tools like cache_store and cache_list.

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?

Provides explicit guidance: 'Use this BEFORE computing expensive results' and explains the benefit of saving tokens and latency. It also clarifies that another agent may have cached the result. No explicit exclusion of when not to use, but the guidance is strong.

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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