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Ticker: Live Event Ticket Market

by com.findticker
OverviewDiscussionsAdmin

List Screening Columns and Presets

list_screen_columns
Read-only

Lists every column a screen_events, create_view or update_view predicate can name, with its meaning, unit and the plan that includes it; view presets lists the preset screens instead. Use it before writing any predicate: column names must be used exactly. Pass search with every word you need in one call (price, demand, inventory, rank, date, category) for only the matching columns. A venue's name is v.venue_name. For the values on one event, use get_event_analytics.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_screen_columns"
  }
}

Input Schema

NameRequiredDescriptionDefault
viewNocolumns (the default) lists the columns. presets lists the preset screens instead: each one's key, name, predicate, sort, the columns it shows, the plan its filter needs and whether this account's plan holds it. Pass a key to screen_events as preset to run one.columns
offsetNoSkip this many columns. The catalog comes back in parts: a cut answer's meta.next gives the offset for the next part.
searchNoOne or more words, as one string ("price demand") or a list (["price", "demand"]): only the columns whose name, group or meaning contains any of them. Omit for the whole catalog.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / search / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "items": {
+      "type": "string"
+    },
+    "type": "array"
+  }
+]
    • changedInput schema / properties / search / description
      Previous value: -"One or more words, e.g. \"price demand\": only the columns whose name, group or meaning contains any of them. Omit for the whole catalog."New value: +"One or more words, as one string (\"price demand\") or a list ([\"price\", \"demand\"]): only the columns whose name, group or meaning contains any of them. Omit for the whole catalog."
    • removedInput schema / properties / search / type
      Removed value: -"string"
  2. Changed1 schema field changed
    • addedInput schema / properties / view
      Added value: +{
+  "default": "columns",
+  "description": "columns (the default) lists the columns. presets lists the preset screens instead: each one's key, name, predicate, sort, the columns it shows, the plan its filter needs and whether this account's plan holds it. Pass a key to screen_events as preset to run one.",
+  "enum": [
+    "columns",
+    "presets"
+  ],
+  "type": "string"
+}
  3. Changed1 schema field changed
    • addedInput schema / properties / search
      Added value: +{
+  "description": "One or more words, e.g. \"price demand\": only the columns whose name, group or meaning contains any of them. Omit for the whole catalog.",
+  "type": "string"
+}
  4. Changed1 schema field changed
    • addedInput schema / properties / offset
      Added value: +{
+  "description": "Skip this many columns. The catalog comes back in parts: a cut answer's meta.next gives the offset for the next part.",
+  "minimum": 0,
+  "type": "integer"
+}
  5. First observed

TDQS

A4.4/5.0
Behavior3/5

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

The annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful operational facts — exact-name matching, per-column plan gating, preset plan availability — but those overlap heavily with the schema's own text, and it says nothing about pagination behavior or result limits beyond what the schema declares.

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?

Front-loaded with the purpose and the mode split, then usage, then a targeted gotcha. Every sentence carries information, though the v.venue_name sentence sits awkwardly mid-paragraph and would read better as a trailing note.

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 read-only catalog endpoint with no output schema, the description covers what the records contain (name, meaning, unit, plan; for presets, key, name, predicate, sort, columns, plan), the prerequisite for using the results, and where to go for the other need. Nothing an agent needs in order to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning beyond it: concrete search terms ('price, demand, inventory, rank, date, category') that show how broad a term should be, and a value hint the schema lacks ('A venue's name is v.venue_name'). That is genuine semantic contribution rather than repetition.

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?

States a specific verb and resource ('Lists every column a screen_events, create_view or update_view predicate can name') and immediately distinguishes the two modes, columns versus presets. Adjacent tools like get_event_analytics are named as out of scope, so the agent can place it without guessing.

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?

Gives an explicit precondition ('Use it before writing any predicate: column names must be used exactly') and an explicit alternative for a different need ('For the values on one event, use get_event_analytics'). It even tells the agent how to batch the query ('Pass search with every word you need in one call').

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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