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Valuein — SEC EDGAR Fundamentals & Smart-Money Data

by io.github.valuein

Create Signal

create_signal

Persist a signal and register it with the firing pipeline. Five condition shapes:

  • filing_event — fire when a ticker files a chosen form type (8-K, 10-K, etc.).

  • ratio_threshold — fire when a ticker's financial ratio crosses a threshold (e.g. interest_coverage < 1.5).

  • watchlist_change — fire on any filing on any ticker in a named watchlist.

  • price_move (Pro+) — fire when a ticker's close-to-close move over 1/5/21 trading days crosses a percent threshold in a given direction.

  • fundamental_change (Pro+) — fire when a standard_concept reports a brand-new period or gets restated.

Delivery channels: email (transactional email), webhook (HMAC-SHA256-signed POST), slack (hooks.slack.com incoming webhook), dashboard (in-app inbox), or agent_run (Pro+ — runs a standing agent team and delivers the finished artifact to your inbox). The cron evaluator runs every 5 minutes. Use test_signal to verify your channel is wired correctly before relying on the cron.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesHuman-readable label.
channelYesDelivery channel for a match — `email` (transactional email), `webhook` (HMAC-SHA256-signed POST to your URL), `slack` (POST to a hooks.slack.com incoming-webhook URL), `dashboard` (in-app inbox, readable via list_signal_inbox), or `agent_run` (Pro+ — runs a standing agent team identified by its id, delivering the finished artifact to your inbox).
conditionYesCondition evaluated each cron tick — a discriminated union of `filing_event` (a watched ticker files a new form), `ratio_threshold` (a financial ratio crosses a comparator/threshold), `watchlist_change` (a named watchlist's membership changes), `price_move` (Pro+ — a close-to-close move crosses a percent threshold), or `fundamental_change` (Pro+ — a standard_concept reports a new period or gets restated).

Output Schema

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

TDQS

A4.1/5.0
Behavior4/5

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

The description discloses behavioral details beyond the minimal annotations: webhook delivery is HMAC-SHA256-signed, slack must be a hooks.slack.com URL, agent_run delivers to inbox, and Pro+ requires specific condition types. The crate creation timeline (cron every 5 minutes) and the tip to test before relying on cron also add transparency. It does not contradict the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description front-loads the core purpose and uses scannable bullets for condition shapes and delivery channels. At roughly 180 words, it is longer than minimal, but the complexity of the tool justifies the detail; every sentence serves a purpose (conditions, channels, cron cadence, testing advice) with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the essential operational context: all condition shapes (except watchlist_restatement), all channel types, Pro+ restrictions, cron frequency, and the test_signal relationship. The missing sixth condition type is a notable gap, but the output schema and the variant's own description in the schema fill that void, so the overall context is strong.

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% (all three parameters have descriptions), so the baseline is 3. The description adds helpful examples like 'interest_coverage < 1.5' and explains the webhook HMAC secret, but it incorrectly states 'Five condition shapes' while the schema actually supports six (missing watchlist_restatement). This omission misleads an agent about the available condition variants, undermining the added value.

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 opening sentence, 'Persist a signal and register it with the firing pipeline,' clearly states the verb and resource. The description then enumerates condition shapes and delivery channels, distinguishing it from sibling tools like delete_signal, test_signal, and list_signals. It also references test_signal as a verification step, reinforcing its unique role.

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 provides clear operational context: it mentions the 5-minute cron evaluator, Pro+ gating for certain condition types, and advises using test_signal before relying on the cron to verify channel wiring. However, it does not explicitly state when not to use this tool (e.g., alternatives for one-off alerts vs standing signals), so it falls short of explicit when-not/alternatives guidance.

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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