Skip to main content
Glama

Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

List Public Theses by User

list_public_theses_by_user
Read-onlyIdempotent

Return the PUBLIC theses + reputation aggregate for a user identified by Stripe customer_id. Used by the /[handle] profile page to render an analyst's track record. Only entries with visibility='public' are surfaced — private theses never leak. Reputation is correct/(correct+wrong) over graded theses; null when n < 5 (sample too small). Sample tier rejected; sp500+ only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax public theses to return. Defaults to 20.
customer_idYesTarget user's Stripe customer_id (resolved by the frontend from the handle).

Output Schema

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

TDQS

A4.5/5.0
Behavior5/5

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

Adds important behavioral details beyond annotations: only public theses, reputation formula, null when n<5, 'Sample tier rejected; sp500+ only'.

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?

Three concise sentences covering purpose, context, and behavior. Front-loaded and efficient.

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 rich schema and annotations, description covers return details (reputation, null condition), access restrictions, and usage context. No gaps.

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 provides full descriptions for both parameters. Description reinforces but does not add new semantics beyond what schema provides.

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 returns public theses and reputation aggregate for a user by customer_id. Specifies usage context (profile page). Distinguishes from siblings by emphasizing 'public' and user-specific nature.

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?

Describes when to use (profile page). Does not explicitly exclude alternatives or provide when-not, but context makes usage clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Valuein — SEC EDGAR Fundamentals & Smart-Money Data toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources