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market

by xyz.sputnikx

daloopa_query

Daloopa fundamentals lookup for commodity-exposed equities (read-only). Returns per-ticker structured fundamentals (revenue, opex, segment splits) sourced from issuer filings. Configure DALOOPA_API_URL + DALOOPA_API_KEY in .env; otherwise pass test_mode=true to receive deterministic mock fixtures suitable for CI and demos. No mutation — fail-open with mock if upstream is unreachable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metricNoOptional metric filter (e.g. "revenue", "segment_revenue", "opex"). Omit to return all available metrics.
tickerYesEquity ticker symbol (e.g. "CLF", "X", "FCX"). 1..16 chars, uppercase recommended.
periodsNoHow many fiscal periods to return (default 4, max 20).
test_modeNoWhen true, return deterministic mock fixtures and skip the external API call entirely.

Schema Changelog

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

  1. Added

TDQS

A4.3/5.0
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 does so well. It discloses read-only behavior, no mutation, fail-open behavior with mock fixtures when upstream is unreachable, deterministic test-mode output, and the underlying data source. This gives an agent an unusually complete safety and failure-mode picture.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, with the core purpose in the first sentence. The following sentences each carry useful operational information. There is minor redundancy between 'read-only' and 'No mutation,' but it is not distracting.

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 4-parameter, no-output-schema, no-annotation tool, the description covers purpose, data source, configuration, test mode, and failure behavior. It does not detail the exact shape or units of returned fundamentals, but the mention of revenue, opex, and segment splits gives an agent enough expectation to invoke and interpret the result reasonably.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents all four parameters with 100% coverage, so the baseline is 3. The description adds mild context for ticker and metric via 'per-ticker structured fundamentals' and example metrics, and it reinforces test_mode's purpose for CI/demos, but it does not add substantial new semantic meaning beyond the schema.

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 opens with a specific verb and resource: 'Daloopa fundamentals lookup for commodity-exposed equities.' It immediately clarifies the return payload ('per-ticker structured fundamentals') and the data source ('issuer filings'), which distinguishes it from sibling price/news tools.

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 intended use case is clear: retrieve fundamentals for commodity-exposed equities. It also gives actionable setup guidance with concrete alternatives ('Configure DALOOPA_API_URL + DALOOPA_API_KEY... otherwise pass test_mode=true'), and explicitly marks the operation as read-only. It does not name alternative sibling tools, but none appear to be close substitutes.

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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TDQS

B3.4/5.0
Disambiguation3/5

Multiple signal tools (front_run_watch, prediction_signals, wave_signal) serve similar purposes and could be confused, though each has a distinct data source. Similarly, soul_insights and soul_stack_feed both present agent-generated content, creating some ambiguity.

Naming Consistency3/5

All names use snake_case, but there's no consistent pattern: some are verb-first (get_prices, search_products), some are brand-prefixed nouns (soul_bounties, wave_portfolio), and mixed usage like daloopa_query and soul_verify. The inconsistency is readable but not predictable.

Tool Count4/5

16 tools for a multi-source market data server is reasonable; there are no outright redundant tools, though a few (think, fusion_capabilities) feel auxiliary. The count is slightly above ideal but well within acceptable bounds.

Completeness2/5

The server provides extensive read-only browsing (soul_bounties, soul_insights) but lacks corresponding action tools like claiming a bounty or purchasing insights, creating dead ends. For a 'market', there are no execute/trade/buy operations, leaving significant gaps for agent workflows.

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