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entroly_dashboard

Displays real-time metrics from the Entroly context engine, including token savings, selection speed, compression ratio, and quality scores.

Instructions

Show the real, live value Entroly is providing to YOUR session right now.

Pulls from actual engine state — not synthetic data. Shows: Money saved: exact $ amounts from token optimization Performance: sub-millisecond selection speed vs API latency Bloat prevention: context compression ratio and memory footprint Selection quality: per-fragment scoring and context sufficiency Safety: duplicates caught, stale fragments filtered

Call this anytime to see exactly what Entroly is doing for you.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 must fully disclose behavior. It states it 'pulls from actual engine state' and lists outputs, but does not explicitly declare it as read-only, idempotent, or non-destructive. The implication is present but not explicit, resulting in a moderate score.

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 with a clear opening sentence and bullet points listing specific metrics. Every sentence adds value, and the content is front-loaded with the primary purpose. No unnecessary words.

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 has no parameters and an output schema exists, the description provides sufficient context about what the tool shows. It covers key metrics but does not address potential costs, rate limits, or performance impact, which would be beneficial but not critical for a simple read-only dashboard.

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 no parameters (input schema is empty), so the description cannot add meaning beyond the schema. Baseline for zero-parameter tools is 4, and the description adds no parameter information, which is acceptable.

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's purpose: 'Show the real, live value Entroly is providing to YOUR session right now.' It lists specific metrics like money saved, performance, bloat prevention, selection quality, and safety, making the purpose concrete and distinguishable from siblings.

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 advises 'Call this anytime to see exactly what Entroly is doing for you,' providing a clear usage scenario. However, it does not explicitly differentiate from sibling tools like get_stats or suggest when not to use it, so a slight deduction is applied.

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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