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Glama

SentimentFX

by org.sentimentfx

list_tickers

List every asset SentimentFX tracks.

Cheap (free — doesn't hit the billing meter).  Returns two groups:
`primary` (5 crypto + 7 FX pairs — the ones with full sentiment coverage
across the primary RSS feeds), and `background` (US equities, ETFs,
commodity futures — coverage is thinner but real).  Use the exact ticker
string from either group as the `ticker` arg to the other tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it delivers: discloses cost behavior ('doesn't hit the billing meter'), return grouping semantics (primary vs background), and coverage quality ('full sentiment coverage' vs 'thinner but real'). No hidden side effects or surprises remain.

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 compact and front-loaded: purpose first, then cost, then output structure, then usage guidance. Every sentence adds unique value without repetition or filler. It is appropriately sized for a simple list tool.

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?

For a zero-parameter list tool with an output schema, the description covers everything needed to call it correctly and use its output meaningfully. It even clarifies subtle domain distinctions (primary vs background coverage) that would otherwise be opaque. Nothing important is missing.

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 schema coverage is trivially complete. The description goes beyond schema by explaining how its output will be used as a ticker argument elsewhere. Baseline 4 is appropriate for a no-parameter tool that still clarifies the output's role in the API.

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?

States a specific verb and resource: 'List every asset SentimentFX tracks.' The description clearly distinguishes this tool from the sibling get_* tools by scope and function. It also adds useful structure about the two ticker groups, making the purpose unmistakable.

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 usage context: use the exact ticker strings from this tool's output as the ticker argument to other tools. This tells the agent when to invoke list_tickers (before calling data tools that need a ticker). It doesn't explicitly name sibling alternates, but the guidance is clear enough for a zero-parameter enumeration tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All SentimentFX toolsInspect
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TDQS

A4.6/5.0
Disambiguation5/5

Each tool targets a distinct resource: raw headlines, daily aggregates, prices, correlation, usage, and ticker universe. Even the two sentiment-adjacent tools (get_sentiment vs get_summary) are clearly separated by granularity and response shape.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern: get_correlation, get_prices, get_sentiment, get_summary, get_usage, list_tickers. The one list_ tool is a conventional collection enumeration and does not break the predictability.

Tool Count5/5

Six tools is well-scoped for a read-only sentiment/price data API. Each tool provides a distinct, necessary capability with no redundancy or bloat.

Completeness5/5

The set covers the full read-only workflow: discover tickers, fetch prices, fetch raw headlines, fetch daily sentiment aggregates, compute the correlation between sentiment and returns, and check API usage. There are no obvious missing operations for the stated domain.

Resources