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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Set Agent Memory

set_agent_memory
Idempotent

Store or update ONE durable memory entry (key → value) for this user so context survives across sessions — preferences, prior conclusions, working context. Replace semantics per key (reusing a key overwrites it). Do NOT store a number you would later cite as a fact: financial figures come from data tools and carry fact_ids; memory values are never treated as verified figures. Caps: 200 entries / 8000 chars per value. Tier: sp500+ (sample rejected).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesMemory key (1–128 chars). Reusing an existing key overwrites its value.
valueYesThe note to remember (≤8000 chars). Never store a figure you would cite as a fact — those come from data tools.

Output Schema

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

TDQS

A4.9/5.0
Behavior5/5

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

Describes replace semantics, caps on entries and value size, and tier restriction. Annotations already indicate idempotentHint=true and destructiveHint=false, but description adds valuable behavioral context without contradiction.

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 sentences with no waste. First sentence states purpose and examples, second sentence warns, third sentence lists limits. Front-loaded with the core action.

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 simple parameters and existence of output schema, the description covers usage guidelines, behavioral traits, and constraints completely. No 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 already has full parameter descriptions (100% coverage). The description adds extra meaning: explains overwrite behavior for key, warns not to store factual numbers in value, and reinforces constraints. Adds value beyond schema.

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?

Explicitly states 'Store or update ONE durable memory entry (key → value)' and distinguishes from siblings like get_agent_memory and delete_agent_memory. Clearly identifies the resource and action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear when-to-use contexts (preferences, prior conclusions, working context) and explicit when-not-to-use (financial figures from data tools). Also mentions tier restriction and caps.

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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