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norman2112

Planview Portfolios Actions MCP Server

by norman2112

discover_financial_plan_info

Retrieve financial plan accounts and periods for a project, with automatic fallback to a reference project if the target plan is unavailable. Optionally skip target read for faster results on new projects.

Instructions

[LOCAL — financial plan discovery with smart fallback. No Beta MCP equivalent exists.]

Discover financial plan information with smart fallback.

Attempts to read the financial plan for the target project. If that fails (e.g., project is too new), falls back to reading a reference project's financial plan to discover available accounts and periods.

Optimized to check config data first (instant), and skip slow target reads for new projects when skip_target_read=True. Use include_entries=False (default for this tool) to avoid large EntryDto arrays and reduce payload size.

Args: entity_key: Target project entity key (e.g., "key://2/$Plan/17291") version_key: Financial plan version key (default: "key://14/1" for Actual/Forecast) reference_entity_key: Optional reference project entity key for fallback. Defaults to None - if not provided and target read fails, returns config data. skip_target_read: If True, skip reading target project's plan (much faster for new projects). Defaults to False for backward compatibility. include_entries: If False, strip EntryDto arrays from each line (default False for smaller response). summary: If True, return only account_keys and period_keys (minimal response). fields: If set, return only these top-level data fields.

Returns: Dict with financial plan data including accounts and periods, or None if unavailable. May return config-based data structure for fast path.

Example: # Fast path for new projects - skip target read, use config or reference plan_info = await discover_financial_plan_info( entity_key="key://2/$Plan/17291", reference_entity_key="key://2/$Plan/3818", skip_target_read=True # Skip slow read for new project )

# Standard path - try target first, then reference
plan_info = await discover_financial_plan_info(
    entity_key="key://2/$Plan/17291",
    reference_entity_key="key://2/$Plan/3818"
)

if plan_info:
    # Extract accounts and periods
    lines = plan_info.get("data", {}).get("Lines", {}).get("FinancialPlanLineDto", [])

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNo
summaryNo
entity_keyYes
version_keyNokey://14/1
include_entriesNo
skip_target_readNo
reference_entity_keyNo
Behavior4/5

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

With no annotations, the description must disclose all behavioral traits. It does so by explaining fallback behavior, optimization paths, config data usage, and return types. However, it does not explicitly state that the tool is read-only or if there are side effects, though it is implied.

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 well-structured with paragraphs, parameter list, returns, and example. It is front-loaded with purpose. It is somewhat long but each sentence adds value, and the organization aids readability.

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?

Given the complexity (7 parameters, no output schema, no annotations), the description is remarkably complete: it covers behavior, parameter details, return values, and provides multiple examples. An agent would have sufficient context to use the tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, but the description compensates by thoroughly explaining each parameter in the Args section, including defaults, behavior, and examples. This adds significant value over the bare 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 clearly states the purpose: 'Discover financial plan information with smart fallback.' It explains the fallback mechanism and distinguishes from siblings like read_financial_plan and load_financial_plan_from_reference by highlighting the smart fallback and configuration data optimization.

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 provides detailed usage guidance: when to use the fast path (skip_target_read=True for new projects) and standard path, and how to reduce payload (include_entries=False). Examples are given. However, it does not explicitly contrast with sibling tools or state when not to use this tool.

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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