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simplefunctions

by io.github.spfunctions

inspect_ticker

STEP 2 OF THE LOOP. Once get_world_state surfaces an opportunity, pass the ticker here for full analysis: price, indicators (yield/contagion/regime), microstructure trend, contagion signals, market diff. Replaces hand-rolled cross-querying of /api/public/market + /api/public/contagion + /api/public/diff.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
diffNoInclude market diff vs prior window (default true)
depthNoInclude live orderbook depth. Default false for cheaper cached agent sweeps.
trendNoInclude microstructure history (default true)
formatNoDefault markdown
tickerYesMarket ticker, e.g. KXFEDDECISION-26DEC10-T0
contagionNoInclude contagion signals (default true)

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / depth
      Added value: +{
+  "default": false,
+  "description": "Include live orderbook depth. Default false for cheaper cached agent sweeps.",
+  "type": "boolean"
+}
  2. Added

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It discloses that this is a consolidated read operation that replaces multiple API calls, and lists the analysis components. It doesn't explicitly say 'read-only' but the verb 'inspect' and the absence of side effects make it safe. The 'STEP 2 OF THE LOOP' context adds workflow value.

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?

Two focused sentences, front-loaded with the step context and core purpose. Every phrase earns its place: 'full analysis' list and the 'replaces' note add value without fluff.

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?

Despite no output schema, the description lists the major return components (price, indicators, trend, contagion, diff) and gives workflow context. It doesn't describe output structure, but the schema's format parameter and the component list provide enough guidance. A slightly richer return description would make it a 5.

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 input schema already covers all parameters with detailed descriptions and default values (100% coverage). The description reiterates the analysis components (yield/contagion/regime, trend, diff) but doesn't add new semantic meaning beyond what the schema provides. Hence baseline 3 is appropriate.

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 tool performs 'full analysis' of a ticker, listing specific components (price, indicators, microstructure trend, contagion signals, market diff). It also positions it as 'STEP 2 OF THE LOOP' and contrasts it with manual cross-querying, effectively distinguishing it from sibling get_* tools.

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?

Explicitly says to use after 'get_world_state surfaces an opportunity' and states it 'Replaces hand-rolled cross-querying' of three endpoints. This gives clear when-to-use and alternative instructions, though it doesn't need to list all siblings.

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