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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Insider Transactions

get_insider_transactions
Read-onlyIdempotent

Form 3 / 4 / 5 / 144 line items for a US public company. Returns each transaction (or initial holding / proposed sale) with the insider's name, role, transaction code, share count, price, and notional. Filters by lookback window, transaction code (P=purchase, S=sale, A=grant, M=option exercise, F=tax withholding, etc.), insider role, and minimum share threshold. Institutional tier only — sample / sp500 / pro return ENTITLEMENT_DENIED with an upgrade link.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum rows to return. Default 100, max 500.
tickerYesStock ticker symbol, e.g. AAPL, MSFT, BRK.B
roles_inNoInsider roles to keep. Omit to include any role.
as_of_dateNoPoint-in-time date (YYYY-MM-DD). Only returns transactions with accepted_at <= this date — eliminates look-ahead bias. When set, lookback_days is ignored.
min_sharesNoMinimum |shares| per transaction. Omit for no floor.
lookback_daysNoHow many days back from today to scan transactions for. Ignored when as_of_date is set.
lineage_detailNoPer-row provenance envelope. 'compact' (default) returns source_filing + source_url. 'full' adds accepted_at. 'off' omits lineage.compact
transaction_codesNoSEC transaction codes to keep (uppercase, single-letter): P=purchase, S=sale, A=grant, M=option exercise, F=tax withholding, G=gift, J=other. Unknown codes are rejected. Omit to include all codes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikYes
rowsYes
_metaYesProvenance envelope — data lineage for every MCP response
tickerYes
company_nameYes
data_age_daysYes
staleness_warningYes

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context, such as the as_of_date eliminating look-ahead bias, interaction between as_of_date and lookback_days, and the fact that certain tiers get a permission error.

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 consists of two well-structured sentences. The first sentence establishes the core purpose and return fields. The second efficiently lists filters and the tier restriction. No unnecessary words.

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 the tool's complexity (8 parameters, 1 required) and the existence of an output schema, the description covers essential behavioral aspects, filter constraints, and tier restrictions. It does not detail the output schema but that is handled separately.

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 100%, but the description goes beyond by explaining the relationship between as_of_date and lookback_days (as_of_date overrides) and briefly describing the lineage_detail options. It compensates for what the schema alone does not provide.

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?

Description clearly identifies the tool's purpose: retrieving Form 3/4/5/144 insider transaction line items for a US public company. It specifies the verb (get) and resource (insider transactions) and distinguishes itself from sibling tools like 'get_insider_sentiment' by detailing the exact data returned.

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?

Description explicitly states the tier restriction ('Institutional tier only') and the error response ('ENTITLEMENT_DENIED' with upgrade link). It does not directly compare to alternative tools or give when-to-use guidance, but the context of insider transactions is well-defined.

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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