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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Score Claim

score_claim
Idempotent

Resolve a claim's outcome. By default auto-grades an auto claim by evaluating its verifiable_condition against SEC fundamentals (confirmed/refuted), or marks it needs_review when it can't be resolved deterministically (judgment, antecedent, or missing data). To record a human/agent judgment instead, pass manual_status (+ optional score/reason). Idempotent — re-scoring the same resolution is a no-op.

Tier: sp500+ (sample rejected).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofNoSnapshot date for the fundamentals window (auto mode). Defaults to today UTC.
claim_idYesId of the claim to resolve.
manual_scoreNoOutcome score in [-1,1] for a manual resolution. Null for non-scored statuses.
manual_reasonNoExplanation for a manual resolution.
manual_statusNoProvide to record a human/agent outcome instead of auto-grading.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
_metaYesProvenance envelope — data lineage for every MCP response
basisYes
claimYes
scoreYes
reasonYes
deduplicatedYes
resolved_statusYes

TDQS

A4.7/5.0
Behavior5/5

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

Annotations give idempotentHint=true; description confirms re-scoring is no-op, explains auto-grading logic and conditions for needs_review. 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?

Four concise sentences, front-loaded with main purpose, each sentence adds distinct value.

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?

Covers necessary details for auto and manual scoring; output schema exists so return values not needed.

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 covers all parameters; description adds context on manual_status mode and optional score/reason, enhancing schema meaning.

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?

Clearly states it resolves a claim's outcome with specific verb 'Resolve'. Distinct from siblings like save_claim, delete_claim, score_due_claims.

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?

Explains auto vs manual modes and idempotency. Could explicitly mention when to use batch scoring tool (score_due_claims) but generally clear.

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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