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Satsuj1n

xp-mcp

by Satsuj1n

screen_assets

Ranks B3 assets (FII, ACAO, ETF) by user-defined criteria with filters and limits. Uses cached brapi data, merges exclusion lists, and outputs educational analysis, not investment advice.

Instructions

Rank B3 assets (FII | ACAO | ETF) against criteria (sort_by, filters, limit). Fetches the universe and per-ticker quote+fundamentals from brapi.dev (cached). Profile's excluded_classes/excluded_tickers are merged with the call's exclude_tickers. Output is educational analysis, not investment advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
criteriaYes
asset_classYesUniverse to screen. FII = fundos imobiliários; ACAO = stocks; ETF = ETFs. TESOURO/RF/FUNDO not supported in v0.4 (no brapi coverage).
exclude_tickersNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.12.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses network behavior ('Fetches the universe and per-ticker quote+fundamentals from brapi.dev (cached)'), merging behavior ('Profile's excluded_classes/excluded_tickers are merged with the call's exclude_tickers'), and output nature ('Output is educational analysis, not investment advice'). This provides substantive insight into side effects and constraints, though it stops short of explicitly stating read-only or idempotency.

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 three sentences, with the first sentence front-loading the core purpose. The subsequent sentences deliver essential behavioral details without fluff. It is compact and information-dense, though slightly longer than necessary.

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 no output schema and no annotations, the description covers the main operational aspects: purpose, data source, caching, exclusions, and output disclaimer. It does not detail the exact return structure, but the phrase 'output is educational analysis' gives a sense of what to expect. The criteria parameter's internal fields are named (sort_by, filters, limit) which helps. Overall, it is fairly complete for a ranking tool.

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?

Schema coverage is only 33% (only asset_class has a description). The description adds meaning to otherwise undocumented parameters: it specifies that 'criteria' contains sort_by, filters, and limit, and explains that exclude_tickers is merged with profile-level exclusions. This compensates for the sparse schema and helps an agent understand what each parameter controls.

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 'Rank' and a clear resource 'B3 assets' with enumerated asset classes (FII, ACAO, ETF). It also specifies the action is against criteria. This distinguishes it from sibling tools like get_market_data or suggest_buys, which are retrieval or suggestion tools, 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 Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for screening/ranking assets but does not explicitly mention when to use this tool versus alternatives or when not to use it. There is no direct contrast with sibling tools like suggest_buys or get_market_data. The intent is inferable but not explicitly stated, so guidance is implied rather than provided.

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