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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Run Saved Workflow

run_workflow
Read-onlyIdempotent

Resolve a saved workflow by id and return a structured execution plan for a single ticker. Each plan entry names a real MCP tool or SOP plus its ticker-substituted arguments; the calling agent invokes them in order, applying any skip_if predicate against the previous step's output.

This tool does NOT execute the steps server-side. It plans; the agent runs. Iterate through plan[] in order, call the named tool/SOP with args, accumulate outputs, and apply each step's skip_if (skip the step when the previous output's path equals equals).

Workflows are private state owned by the calling user. Sample-tier callers are rejected. Pair with list_workflows (frontend) to discover available workflow_ids.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerNoUS-listed ticker the workflow should run against, e.g. 'AAPL'. Pass either `ticker` (single) or `tickers` (batch up to 50). Exactly one is required.
tickersNoBatch mode — array of US-listed tickers, up to 50. When provided, the response has `plans[]` (one plan per ticker) instead of `plan`. Parity with the frontend batch-runner so agents can request 'plan over my watchlist' in a single call.
workflow_idYesWorkflow id returned by the frontend workflow builder.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metaYesProvenance envelope — data lineage for every MCP response
planYes
plansYes
tickerYes
workflowYes
instructionsYes

TDQS

A4.4/5.0
Behavior5/5

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

The description fully delineates the tool's behavior beyond annotations: it plans but does not execute, describes the plan structure with `skip_if` predicates, explains that workflows are private per user, and notes that sample-tier callers are rejected. Annotations (readOnlyHint, idempotentHint, destructiveHint) are consistent and the description adds rich context about the execution model.

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 the most critical information upfront (purpose and non-execution warning). It then details usage pattern and restrictions. Every sentence adds value, but it could be slightly tightened (e.g., combining the first two sentences into one).

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 tool's complexity (workflow planning, batch mode, skip_if logic), the description is complete. It addresses how the agent should use the output (iterate plan, call tools, apply skip_if), restrictions (sample-tier), and integration with list_workflows. An output schema exists, so return values are handled elsewhere.

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?

Schema description coverage is 100%, so baseline is 3. The description adds some context about ticker vs tickers batch mode (maximum 50) and workflow_id source, but it largely reiterates the schema. It doesn't add significant new meaning beyond what the schema already provides.

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 tool's purpose: 'Resolve a saved workflow by id and return a structured execution plan for a single ticker.' It distinguishes from siblings by specifying that it plans rather than executes, and it covers both single and batch modes. The verb 'resolve' and resource 'workflow' are specific.

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 explicitly warns that the tool does NOT execute steps, but plans them, and directs the agent to iterate through the plan and call tools/SOPs. It also suggests pairing with list_workflows. While it doesn't list explicit alternatives, the guidance is clear and actionable. A slight improvement would be to mention 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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TDQS

A4/5.0
Disambiguation5/5

Each tool has a distinct purpose with detailed descriptions that clarify differences. Overlaps like get_peer_comparables vs screen_universe are well-differentiated by scope (single company vs cross-sectional). Similarly, get_insider_sentiment vs get_smart_money_flow are clearly distinguished by data sources and methodology.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (e.g., create_report, get_financial_ratios, delete_alert). No mixing of conventions or inconsistent verbs.

Tool Count2/5

With 69 tools, the count far exceeds the 25+ threshold for 'too many'. While the domain is broad, the sheer volume likely overwhelms agents and increases selection complexity.

Completeness4/5

The tool set covers a wide range of SEC filings, ratios, smart-money data, alerts, reports, and more. Minor gaps exist (e.g., no options or detailed debt data), but most analyst workflows are supported.

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