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equibles

by io.github.daniel3303

Index Rebalance Forecast

GetIndexForecast
Read-only

Apply an index's published entry rules and return candidates with rule-by-rule evidence. S&P results are SCREENS because a committee chooses additions; the S&P 500 adds versioned 90-day empirical join probabilities for eligible candidates and exit probabilities for every member. They are estimates, not guarantees. Russell and Nasdaq-100 are PROJECTIONS decided by published rankings. A non-member with a missing figure has no entry verdict. An unmeasured member stays out of deterministic departure buckets, while the S&P 500 gives it the neutral exit baseline. The Dow has no quantitative rule or forecast. Each model revision is immutable. A model-version change may append a higher revision for the same trading day, and readers use the highest revision.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
indexYesIndex name or slug, for example "S&P 500", "nasdaq-100" or "Russell 2000". The Dow is not forecastable.
maxResultsNoMaximum companies to return per bucket (default 25, max 1000).

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only establish read-only and non-destructive behavior. The description adds essential behavioral detail: estimates are not guarantees, missing figures produce no entry verdict, unmeasured members are handled differently across indices, and model revisions are immutable with a highest-revision rule. This materially changes how an agent should interpret results.

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 front-loaded with the core operation and then organized by index family, edge cases, and revision semantics. Although dense, every sentence contributes a distinct and material constraint; there is no redundant filler.

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?

This is a complex endpoint with no output schema, yet the description covers the output form (candidates with evidence, probabilities, departure buckets), index-specific forecast certainty, edge-case behavior, and versioning. That is sufficient for an agent to invoke and interpret the tool correctly.

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 both parameters with 100% coverage, including accepted index forms, the Dow limitation, and maxResults bounds. The description reinforces index-level semantics but does not add new parameter syntax or formatting details, so the baseline 3 is appropriate.

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 first sentence states a specific verb ('Apply'), a resource ('an index's published entry rules'), and a concrete deliverable ('return candidates with rule-by-rule evidence'). It also distinguishes this from sibling tools by framing it clearly as a forecast rather than a historical change report.

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 gives explicit guidance on when results are SCREENS vs PROJECTIONS and states that the Dow has no forecast, so an agent knows where the tool applies and where it does not. It does not explicitly name alternative sibling tools for actual index changes, which keeps it from a 5.

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
Disambiguation4/5

Most tools have clearly distinct purposes, with detailed descriptions that cross-reference related alternatives. A few near-duplicate names could cause misselection, notably SearchDocument versus SearchDocuments and GetCftcPositioning versus GetLatestCftcPositioning.

Naming Consistency5/5

Tool names consistently follow a VerbNoun camelCase pattern: Get for retrievals, Search for discovery, List/Read for document access, and Add/Close/Remove/Update/Watch/Create/Delete for portfolio mutations. Despite the large count, there is no mixing of naming conventions or unpredictable verb styles.

Tool Count1/5

108 tools is an extreme surface area, far beyond the 3-15 well-scoped range and well past the 25+ threshold. Even for a broad financial data platform, this creates a heavy selection burden and substantial context overhead for agents.

Completeness4/5

The server covers an unusually wide domain: prices, fundamentals, SEC filings, options, insider activity, 13F holdings, short interest, macro data, funds, IPOs, and full portfolio lifecycle management. Notable gaps remain, such as a basic company profile/ticker-resolution tool, dividend history, and analyst estimates, so it is not a perfect 5.

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