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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

Test Signal (synthetic fire)

test_signal

Fire a synthetic notification through the signal's configured channel. Use this immediately after create_signal to verify the channel (email address valid / webhook URL reachable + HMAC verification on the receiver). The synthetic fire is logged as attempt=1 channel='test' so it doesn't affect the real fire counter — the next genuine match still fires normally.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
signal_idYesIdentifier of the signal to fire a synthetic test notification through, as returned by create_signal or list_signals.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
_metaYesProvenance envelope — data lineage for every MCP response
outcomeYes
signal_idYes
status_codeYes
channel_typeYes
error_messageYes

TDQS

A4.5/5.0
Behavior5/5

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

Annotations (readOnlyHint=false, destructiveHint=false) are minimal, so the description carries the burden. It discloses side effects: logged as attempt=1 channel='test', no impact on real fire counter, and next genuine match fires normally. This is rich behavioral context beyond what annotations provide.

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, each earning its place: action, usage timing/purpose, and side-effect explanation. Front-loaded with the verb and resource, no wasted 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?

For a simple one-parameter tool with an output schema, the description covers when to use, what it does, and behavioral implications. Nothing essential is missing, and output schema handles return-value documentation.

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 covers 100% of the single parameter signal_id with a description referencing create_signal/list_signals. The tool description adds no new parameter syntax or formatting details, so baseline 3 applies.

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 action ('Fire a synthetic notification') and the resource ('through the signal's configured channel'). It distinguishes itself from sibling tools like test_rule by specifying 'synthetic' and channel verification, making its purpose unambiguous.

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?

Explicit when-to-use guidance is present ('Use this immediately after create_signal'), with a clear reason (verify channel). It does not mention when not to use or name alternative tools, so it falls short of a full 5.

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.