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cart_add

Stage saved query scenes into the Bhoonidhi cart using a slug, optionally selecting specific scenes. Routes each scene to its required cart and reports staged or failed counts.

Instructions

Stage a saved query's scenes to the Bhoonidhi cart.

Give the slug from save_query or list_queries. Each scene is routed to the cart its access type needs (ready / on-order / priced); select narrows to specific scenes (1-based indices or scene IDs). Needs a login (see auth_status). Use this for on-order and priced scenes; priced ones still need purchasing on the portal afterwards. Returns counts of what was staged and what failed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes
selectNo

Schema Changelog

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

  1. First observedv0.2.0

TDQS

A4.8/5.0
Behavior5/5

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

With zero annotations, the description carries the full burden and meets it: it discloses the auth requirement, the routing behavior by access type (ready/on-order/priced), the non-obvious limitation that priced scenes still require purchasing on the portal afterward, and the return shape (counts of staged and failed). None of this could be inferred from the name or bare schema.

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?

Five short sentences, each carrying distinct information: purpose, slug provenance, routing and select mechanics, login prerequisite, usage guidance with limitation, and return value. The purpose is front-loaded and no sentence is filler.

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 moderate-complexity tool with no annotations and no output schema, the description covers everything needed to call it correctly: what it does, where the required slug comes from, selection semantics, required auth, workflow caveats, and return format. The only minor ambiguity, whether ready scenes should also be added here, does not block correct invocation.

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

Parameters5/5

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

Schema description coverage is 0%, and the description fully compensates: slug is explained as coming from save_query or list_queries, and select is clarified as narrowing to specific scenes via 1-based indices or scene IDs. The bare schema provides only the titles 'Slug' and 'Select', so the description is the sole source of semantic meaning.

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?

Opens with a specific verb-resource-destination statement: 'Stage a saved query's scenes to the Bhoonidhi cart,' which names the action, the input resource, and the target. It is immediately distinguishable from siblings like cart_remove, cart_list, and save_query by referencing saved-query scenes and the staging-to-cart behavior.

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?

Gives explicit when-to-use context ('Use this for on-order and priced scenes'), a prerequisite ('Needs a login (see auth_status)'), and an input source ('Give the slug from save_query or list_queries'). It stops short of a 5 because it never names alternative tools for exclusion, e.g., what to use for ready scenes or for completing purchases.

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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