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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Get Saved Thesis

get_thesis
Read-onlyIdempotent

Fetch a single saved thesis by its id. Returns the full record including outcome (if scored). Returns NOT_FOUND if the id is unknown or belongs to another user. For the claims composing a thesis use list_claims_for_thesis; for an individual claim use get_claim. Tier: paid + free (sample rejected).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thesis_idYesId returned by `save_thesis` or `list_theses`.

Output Schema

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

TDQS

A4.3/5.0
Behavior4/5

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

Adds details beyond annotations: returns full record including outcome if scored, and NOT_FOUND for unknown or other user's thesis. Annotations already indicate readOnly, idempotent, non-destructive; description complements them.

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 sentences, each delivers value: action, behavior, alternatives, tier. No fluff, front-loaded with primary purpose.

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 purpose, behavior, errors, alternatives, and tier. Single parameter fully described in schema. Output schema exists (not shown but present). Complete for a simple fetch 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 already fully describes thesis_id. Description does not add parameter semantics but includes relevant error behavior. With 100% schema coverage, 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?

Clearly states action (fetch), resource (single saved thesis), and identifier (by id). Explicitly distinguishes from siblings by directing to list_claims_for_thesis and get_claim for related but different functionality.

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?

Provides explicit alternatives for claims composing a thesis and individual claims. Also mentions tier restrictions. Lacks explicit context like 'use after listing theses' but sibling differentiation is strong.

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.