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echocache

echocache

by kskurtveit
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

cache_stats

Inspect cache analytics: entry/edge counts, exact-match hit rate, semantic query hits/misses, and tokens served. Use these metrics to evaluate caching effectiveness and identify true token savings.

Instructions

Cache analytics: entry/edge counts, exact-match hit rate, queryHits/queryMisses for semantic recall, and tokensServed — the token count handed back from cache. Note that tokensServed equals tokens saved only for entries that stand in for work which would otherwise be regenerated; serving a cached file read costs the same tokens as re-reading the file, so it saves nothing.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "cache_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It adds a genuinely useful behavioral nuance: tokensServed equals tokens saved only for entries avoiding regeneration, not for cached file reads. It does not explicitly state read-only behavior, but 'analytics' and the absence of mutation verbs imply no side effects.

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 tight sentences with the label front-loaded in 'Cache analytics'. The first sentence enumerates the return metrics; the second adds a necessary caveat about tokensServed. No filler.

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?

For a zero-parameter analytics tool with no annotations or output schema, the description covers the main return values and even clarifies a subtle metric. It does not specify the exact response container or explicitly state that the call is read-only, but those are minor gaps for this simple tool.

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?

The tool has zero parameters, so parameter documentation is moot. The rubric's baseline for 0 params is 4, and the description needs no clarifification of parameter semantics.

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?

The description identifies the tool as 'Cache analytics' and lists concrete metrics (entry/edge counts, exact-match hit rate, queryHits/queryMisses, tokensServed), making its role clear. It is distinguishable from the sibling get/set/query/related/invalidate tools by being an analytics/stats tool, though it lacks an explicit verb like 'retrieves'.

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?

The description does not mention siblings or exclusions, but the phrase 'Cache analytics' plus the metric list implies this is the tool to use when cache statistics are needed. There is no explicit when-not-to-use guidance, so it stops short of a 4.

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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