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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Smart Money Flow (composite)

get_smart_money_flow
Read-onlyIdempotent

Composite flow score on [-100, +100] aggregating insider transactions, 13F institutional Δ-shares vs the prior quarter, and SC 13D/13G blockholder changes over a lookback window. Each component normalised independently, then combined with configurable weights (default: institutional 0.4, blockholder 0.4, insider 0.2). Returns per-component attribution so an agent can see WHY the score is what it is — not just the headline number. NOTE: the institutional component is a QoQ share-change signal computed over the top-5 13F filers on a MATCHED current-vs-prior basis (a filer only counts when its prior-quarter book is observable), NOT the issuer's complete institutional book — treat the score as a directional signal, not an exact flow. coverage.coverage_confidence (0–1) reports how much of that basis had a real prior quarter; when it is 0 the institutional component is forced to 0 so a 13F ingestion gap can never surface as a false max-conviction buy. See the coverage block for holder coverage + staleness. The score is a unitless composite, not a dollar figure. Institutional tier only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesIssuer ticker symbol.
as_of_dateNoPoint-in-time cutoff (YYYY-MM-DD) applied to all three legs (institutional, insider, blockholder) via SEC accepted_at — filings accepted after this date are excluded so the composite is computed with zero look-ahead. Omit for the latest knowable signal.
lookback_daysNoLookback window for insider + blockholder components. Default 90.
weight_insiderNoWeight applied to the insider component (0–1).
weight_blockholderNoWeight applied to the blockholder component (0–1).
weight_institutionalNoWeight applied to the institutional component (0–1).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cikYes
_metaYesProvenance envelope — data lineage for every MCP response
tickerYes
weightsYes
coverageYesHonesty block: the institutional signal is computed from a top-N 13F slice with a top-5-filer matched basis. Surfaces holder coverage + staleness so the composite is never read as the issuer's complete book.
as_of_dateYesThe point-in-time cutoff actually applied (echo of the as_of_date input). Null when no PIT cut was requested — never the reporting period_end fabricated as a cutoff.
componentsYes
period_endYesThe institutional 13F REPORTING period — NOT a point-in-time cutoff.
company_nameYes
composite_scoreYes
insider_componentYes
blockholder_componentYes
institutional_componentYes

TDQS

A4.7/5.0
Behavior5/5

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

Annotations indicate readOnlyHint=true and destructiveHint=false, which the description aligns with. The description adds significant behavioral context beyond annotations: zero look-ahead via as_of_date, coverage_confidence forcing institutional component to zero if missing, and the score being unitless. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with the main purpose at the start, followed by details on components, weights, and caveats. Every sentence adds necessary information without redundancy. It is appropriately sized for a complex tool.

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 (three components, configurable weights, caveats), the description covers all essential aspects: range, components, normalization, weights, institutional limitation, coverage_confidence, and the nature of the score. It is complete and leaves no significant gaps.

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%, so the baseline is 3. The description adds meaning by explaining how components are normalized and combined, and the institutional caveat (matched top-5 filers) that isn't in the schema. This provides value beyond the parameter descriptions.

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 that the tool computes a composite flow score on a scale of -100 to +100, aggregating insider, institutional, and blockholder signals. It distinguishes itself from sibling tools like get_insider_transactions and get_institutional_holdings by combining them into one score with configurable weights.

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 context on when to use the tool, such as for directional smart money flow analysis, and includes important caveats like the institutional component being based on matched top-5 filers, not the complete institutional book. However, it does not explicitly state when not to use it or directly compare with alternatives.

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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