compareThe 16 percentile scores + P3 + 1Y price change for 2-5 tickers as one compact matrix (rows = metrics, columns = tickers). Use when weighing names against each other; percentiles make the comparison fair across sectors and sizes.
| Name | Required | Description | Default |
|---|---|---|---|
| tickers | Yes | 2-5 US tickers |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context by specifying the exact metric composition (16 percentile scores + P3 + 1Y price change) and the matrix layout (rows = metrics, columns = tickers), which an agent could not infer from annotations or the minimal schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two dense sentences carry the full purpose, output shape, and usage context with no filler. The core output definition is front-loaded, and every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read-only comparison tool, the description is largely complete: it defines the input range, the exact metrics, the matrix orientation, and the intended use case. The only minor gap is that 'P3' is not expanded, which could confuse an agent unfamiliar with the domain, but this does not prevent correct tool selection or invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the only parameter, tickers, as '2-5 US tickers' with minItems and maxItems constraints, so schema coverage is 100%. The description reinforces the 2-5 range but does not add meaningful semantic detail beyond what the schema provides, matching the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific operation and resource: comparing fingerprints side by side, with a precise output definition (16 percentile scores + P3 + 1Y price change for 2-5 tickers as a matrix). This clearly distinguishes it from siblings like fingerprint or peers, which would not produce a multi-ticker comparison matrix.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use it: 'when weighing names against each other' and explains why percentiles are appropriate for fair comparison. It does not name alternatives or give exclusion conditions, but the context is clear enough for an agent to select this tool over the listed siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool owns a distinct analytical niche: single-stock character, multi-ticker comparison, market regime, business peers, co-movement cluster, and universe screening. The only near-overlap (fingerprint's peer list vs peers) is explicitly resolved by describing peers as the deeper standalone lookup.
All names are lowercase and stylistically consistent, but there is no verb_noun pattern: compare and screen are verbs while market_regime, peers, and theme_cluster are noun phrases. The mixed grammar is readable but not a strongly predictable naming convention.
Six tools is tightly scoped for a stock-character research server; each tool covers a distinct user workflow and none feels redundant. The count is well within the ideal range and does not burden an agent with overlapping endpoints.
The set covers the full intended workflow: assess market context, inspect a single stock, compare tickers, identify true peers and co-movement groups, and screen the universe on every available metric. There are no obvious dead ends or missing operations for a read-only analytics domain.