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simplefunctions

by io.github.spfunctions

configure_heartbeat

Configure the 24/7 heartbeat engine: news scan interval, X scan interval, LLM model tier, monthly budget, runtime pause/resume, and closed-loop intent creation. Agent can speed up monitoring during high volatility or slow down to save budget.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
apiKeyYesSimpleFunctions API key. Get one at https://simplefunctions.dev/dashboard/keys
pausedNoPause/resume heartbeat
thesisIdYesThesis ID
xIntervalMinNoX/social scan interval in minutes (60-1440, default 240)
evalModelTierNoLLM model for evaluations
closedLoopExitNoEnable/disable closed-loop exit intent creation
closedLoopEntryNoEnable/disable closed-loop entry intent creation
newsIntervalMinNoNews scan interval in minutes (15-1440, default 240)
monthlyBudgetUsdNoMonthly budget cap in USD (0 = unlimited)

Schema Changelog

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

  1. Changed4 schema fields changed
    • addedInput schema / properties / closedLoopEntry
      Added value: +{
+  "description": "Enable/disable closed-loop entry intent creation",
+  "type": "boolean"
+}
    • addedInput schema / properties / closedLoopExit
      Added value: +{
+  "description": "Enable/disable closed-loop exit intent creation",
+  "type": "boolean"
+}
    • changedInput schema / properties / evalModelTier / enum
      Previous value: -[
-  "cheap",
-  "medium",
-  "heavy"
-]New value: +[
+  "cheap",
+  "base",
+  "medium",
+  "heavy"
+]
    • changedInput schema / properties / newsIntervalMin / description
      Previous value: -"News scan interval in minutes (15-1440, default 60)"New value: +"News scan interval in minutes (15-1440, default 240)"
  2. First observed

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden for behavioral disclosure. It lists the settings and hints at operational effects (monitoring speed, budget), but it does not explain side effects, persistence, reversibility, or prerequisites like requiring an existing thesisId beyond what the schema already states.

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 extremely concise: two sentences. The first sentence defines scope via a list of configurable aspects, and the second provides a practical use case. No unnecessary words or repetition.

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?

Given the tool's complexity (9 parameters, mutation) and the absence of both annotations and an output schema, the description is adequate but incomplete. It tells what the tool does and when to use it, but does not mention reading the current config first or the detailed consequences of changes.

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% with detailed descriptions for all 9 parameters, so the baseline is 3. The description adds a general operational framing (e.g., speed vs. budget) but does not deepen understanding of individual parameters beyond 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 identifies the tool's action ('Configure') and resource ('24/7 heartbeat engine'), then enumerates the specific configurable settings (news scan interval, X scan interval, LLM model tier, monthly budget, runtime pause/resume, closed-loop intent creation). This distinguishes it from sibling read-only tools like get_heartbeat_config and get_heartbeat_status.

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 a clear usage context: the agent can use it to speed up monitoring during high volatility or slow down to save budget. However, it does not explicitly mention alternatives (e.g., using get_heartbeat_config to read current settings) or state when not to use the tool.

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.

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