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simplefunctions

by io.github.spfunctions

create_intent

Declare an execution intent: "buy X when condition Y, expire at Z." Intents are the single gateway for all order execution. The local runtime daemon evaluates triggers and executes via user's Kalshi/Polymarket keys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
venueYesExchange venue
actionYesTrade action
apiKeyYesSimpleFunctions API key. Get one at https://simplefunctions.dev/dashboard/keys
sourceNoIntent source: agent, manual, ideaagent
expireAtNoISO timestamp when intent expires (default: +24h)
marketIdYesMarket ticker (e.g. KXFEDDEC-25DEC31-T100)
maxPriceNoMax price per contract in cents (1-99). Omit for market order.
sourceIdNoSource reference (idea ID, thesis ID, etc.)
directionYesContract direction
rationaleNoWhy this trade — logged for audit trail
autoExecuteNoAuto-execute without later human confirmation. Defaults to false unless explicitly set true.
marketTitleYesHuman-readable market name
triggerTypeNoWhen to executeimmediate
triggerPriceNoPrice trigger threshold in cents (for price_below/price_above)
targetQuantityYesNumber of contracts

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / autoExecute / description
      Previous value: -"Auto-execute without human confirmation"New value: +"Auto-execute without later human confirmation. Defaults to false unless explicitly set true."
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Given no annotations, the description discloses meaningful behavioral context: a local runtime daemon evaluates triggers and executes via the user's Kalshi/Polymarket keys. This conveys the asynchronous execution model and key-based authorization. It does not mention return values or confirmation steps, but the disclosed mechanism goes beyond a simple tautology.

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?

The description is exactly two sentences, front-loaded with purpose, and includes a concrete example plus architectural context. Every word earns its place; there is no redundancy or fluff.

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

Completeness3/5

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

The description explains the core concept and execution model, and the schema covers parameters thoroughly. However, with no output schema, the description lacks any indication of what the tool returns or the immediate result of creating an intent (e.g., intent ID, status). For a complex tool with 15 parameters, this gap is notable.

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?

The schema provides 100% description coverage for all 15 parameters, including enums, defaults, and examples. The description adds no additional parameter semantics beyond the illustrative 'buy X when condition Y, expire at Z' example, which maps to action, targetQuantity, triggerType, and expireAt but does not enrich the 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?

The description clearly names the operation 'Declare an execution intent' and states it is the single gateway for all order execution, distinguishing it from sibling tools like cancel_intent or get_orders. The verb 'Declare' is specific and the resource is 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?

The phrase 'single gateway for all order execution' gives clear context that this is the go-to tool for placing orders, implying use for execution workflows. However, it does not explicitly name alternatives or state when not to use it, so it falls just short of a 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

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as multiple market query tools (scan_markets, screen_markets, get_market_detail, get_market_diff, get_market_history, inspect_ticker) and legislative tools (legislation, get_legislation, list_legislation, query_gov). Aliases like get_heartbeat_config/get_heartbeat_status and explore_public/explore_theses add further confusion. An agent would struggle to select the correct tool without deeply reading each description.

Naming Consistency3/5

Most tools follow a verb_noun pattern (get_, list_, create_, update_), but there are notable deviations: 'legislation' lacks the 'get_' prefix, 'stt' and 'tts' are acronyms, 'monitor_the_situation' is a full phrase, and 'x_account/x_news/x_volume' use a non-standard prefix. The overall style is readable, but the mixed conventions reduce predictability.

Tool Count1/5

108 tools is extreme for any server, even one covering prediction markets, trading, portfolio management, forum, skills, and speech. The massive surface area overwhelms agents and makes the server feel more like a platform than a coherent toolkit. This many tools inevitably leads to redundancy and maintenance burden.

Completeness4/5

The server covers an impressively broad domain: market data, thesis management, intents, strategies, positions, portfolio, forum, skills, legislative and economic queries, and audio/visual processing. Minor gaps exist (e.g., no delete for skills/theses, no update for some portfolio items) but core workflows are well-supported. Overall lifecycle coverage for most entities is strong.

Resources