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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

List Claims for Thesis

list_claims_for_thesis
Read-onlyIdempotent

List the claims composing a thesis, each with its role (supports/refutes/context). This is how you read a thesis as the structured argument it is — its supporting and disconfirming claims with their current statuses. Archived claims are omitted. Tier: paid + free (sample rejected).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thesis_idYesId of the thesis whose claims to list.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_metaYesProvenance envelope — data lineage for every MCP response
itemsYes

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already include readOnlyHint, idempotentHint, and destructiveHint, so the description carries less burden. It adds context about omitted archived claims and the return of roles/statuses, which is complementary and adds value.

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?

Two concise sentences, front-loaded with key information. No extraneous words.

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 presence of an output schema and high schema coverage, the description adequately explains what the tool returns (claims with role and status) and what it omits (archived claims). Sufficient for a read-only listing tool.

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% and the parameter 'thesis_id' has a clear description. The tool description does not add further parameter details; 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 lists claims for a specific thesis, including their roles (supports/refutes/context) and statuses. It distinguishes from siblings like 'list_claims' (general) and 'get_claim' (single) by scoping to a thesis.

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 implies usage for reading a thesis as a structured argument. It mentions archived claims are omitted, providing a constraint. However, it does not explicitly state when not to use this tool versus alternatives like 'list_claims' or 'get_thesis'.

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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