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DalalOS: Indian Stock Market Research (NSE/BSE)

by in.dalalos
OverviewDiscussionsAdmin

Run a preset screen

run_preset_screen
Read-onlyIdempotent

Use this when the user wants the latest result of a named ready-made screen from list_preset_screens.

Return the last nightly-precomputed result for one registered preset screen.

`name` must be one of the names returned by list_preset_screens. A preset that has never
been computed yet returns an empty result with reason_code "no_data". Cache-only — this is
the stored output of an equivalent screen_stocks(filters=...) call, not a live query.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

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

Input Schema

NameRequiredDescriptionDefault
nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "additionalProperties": true,
-      "title": "Result",
-      "type": "object"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "run_preset_screenOutput",
-  "type": "object"
-}New value: +null
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "result": {
+      "additionalProperties": true,
+      "title": "Result",
+      "type": "object"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "title": "run_preset_screenOutput",
+  "type": "object"
+}
  3. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (readOnly/idempotent/closed-world), it discloses freshness semantics ('last nightly-precomputed'), that the call is served from cache rather than computed live, and the edge case that an uncomputed preset returns an empty result with reason_code 'no_data'. These are exactly the behaviors an agent needs and none are in 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 when-to-use guidance is front-loaded and every sentence carries content. The mid-sentence line breaks and indentation are formatting artifacts rather than content, but there is no filler or redundancy.

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?

With no output schema, the description covers the important return semantics (nightly cached result, empty result plus reason_code). It does not describe the shape of a non-empty result, which would be the last remaining gap for an agent composing a response.

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 0%, so the description must carry the parameter meaning — it does, stating that `name` must be one of the names returned by list_preset_screens. It stops short of stating whether matching is exact/case-sensitive or what happens for an unrecognized name.

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 ('Return the last nightly-precomputed result for one registered preset screen') and explicitly distinguishes itself from both list_preset_screens (the source of names) and screen_stocks(filters=...) (the live equivalent). An agent can pick it correctly without opening the schema.

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?

'Use this when the user wants the latest result of a named ready-made screen from list_preset_screens' gives an explicit trigger, and 'Cache-only — this is the stored output of an equivalent screen_stocks(filters=...) call, not a live query' tells the agent when to prefer screen_stocks instead.

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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