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digikala-mcp

Prepare Account Cart Change

prepare_account_cart_change

Builds an approval-gated, five-minute cart change plan for adding, updating, or removing Digikala items, validating required IDs and caps before host execution; does not mutate remotely.

Instructions

Trusted backend: prepare a five-minute token-account cart plan; no remote mutation.

add needs product_id + offer_id; update needs cart_item_id + final quantity; remove needs cart_item_id. Host must present and approve the exact plan before execution. Amount/unit caps apply. Token stays private to the host; never falls back to keyring.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
changeYes
session_tokenYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
offerYes
titleYes
actionYes
limitsYes
plan_idYes
expires_atYes
product_idYes
cart_item_idNo
projected_itemsYes
target_quantityYes
previous_quantityYes
projected_total_rialYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: five-minute token lifetime, that this call performs no remote mutation (mutation happens outside it), mandatory human approval of the plan, amount/unit caps, and token privacy including no keyring fallback. These are exactly the kind of constraints annotations (readOnlyHint=false, destructiveHint=false, openWorldHint=true) cannot express.

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?

Three compact lines, front-loaded with the identity and the safety constraint, then per-action requirements, then approval and token handling. Every clause carries information an agent needs; no 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?

Despite a nested-object schema with zero param descriptions and an output schema that covers return values, the description supplies the action-conditional semantics, the approval gate, caps, and token lifetime. Nothing essential for correct invocation appears missing.

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%, so the description must carry the load, and it does: it documents the conditional field requirements per action enum value (add/update/remove), which the schema's anyOf/default structure cannot convey. This is meaningfully more than the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (prepare) and resource (token-account cart plan) and explicitly marks it as non-mutating ('no remote mutation'), which separates it from add_to_account_cart/update_account_cart_item siblings. It does not name prepare_cart_change (the likely non-account counterpart), so sibling differentiation is inferential rather than stated.

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 concrete per-action requirements (add needs product_id + offer_id; update needs cart_item_id + final quantity; remove needs cart_item_id) and specifies the host must present and approve the exact plan before execution, implying the two-phase prepare-then-execute flow. It does not name the follow-up tool or explicitly say when to prefer this over the direct mutation tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.