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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Insider Sentiment (composite)

get_insider_sentiment
Read-onlyIdempotent

Role-weighted insider sentiment score on a fixed [-100, +100] scale for a single issuer over a lookback window. Role weights: CEO/CFO = 3.0 (via officer_title pattern), other NEO Officer = 2.0, 10%-Owner = 1.5, Director = 1.0. P = +1, S = -1; option exercises, grants, and tax withholdings are neutralised. Cluster flag = TRUE when ≥3 distinct insiders transacted within any 30-day window inside the lookback. Institutional tier only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesIssuer ticker symbol.
lookback_daysNoDays back from today to scan transactions for. Default 180.
cluster_window_daysNoSliding window for the cluster_flag detection. Default 30 days.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikYes
_metaYesProvenance envelope — data lineage for every MCP response
tickerYes
buy_countYes
sell_countYes
cluster_flagYes
company_nameYes
lookback_daysYes
total_buy_usdYes
total_sell_usdYes
sentiment_scoreYes
top_contributorsYes
total_buy_sharesYes
total_sell_sharesYes

TDQS

A3.7/5.0
Behavior4/5

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

Annotations declare readOnlyHint, idempotentHint, and destructiveHint, already indicating safe, idempotent behavior. The description adds significant context: the scale range, role weights, transaction type handling (P=+1, S=-1, neutralized items), and cluster flag logic. No contradictions.

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 concise and well-structured, covering key aspects in a few sentences. It avoids unnecessary words but could be slightly more streamlined. Still highly effective.

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 presence of an output schema, the description does not need to detail return values. It explains the scale, weights, transaction handling, cluster flag, and the required tier. It covers major functional aspects, though edge cases (e.g., no transactions) are not mentioned.

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 coverage is 100% with all parameters described. The description does not add parameter-specific details beyond the schema; it explains the overall algorithm but not syntax or constraints. 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 description clearly states the tool computes a role-weighted insider sentiment score on a fixed scale for a single issuer over a lookback window. It distinguishes from sibling like get_insider_transactions by focusing on a composite sentiment score rather than raw transaction data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives such as get_insider_transactions or other sentiment indicators. The description details the computation but does not provide context for selection, exclusion criteria, or prerequisites.

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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