Extracts live product catalogs, pricing tiers, SKU variants, and stock availability from any Shop.
Scored across 2 tools
The two tools have entirely distinct purposes: one extracts storefront data and the other reports the agent's billing/quota status. No overlap in function or trigger conditions.
Both names use consistent snake_case with a leading verb (extract_, get_) followed by a descriptive noun phrase. The pattern is predictable even across only two tools.
Only two tools for a server branded as 'Competitive Intelligence,' and one of them is a billing utility rather than an intelligence capability. The surface is too thin for the advertised scope and mixes monetization plumbing with domain functionality.
Beyond a single-store extraction call there is no comparison, historical tracking, price-change monitoring, or multi-store/batch capability — core expectations for competitive intelligence. Coverage is effectively one-shot extraction plus a wallet check, leaving obvious gaps.
Extracts live product catalogs, pricing tiers, SKU variants, and stock availability from any Shopify or e-commerce storefront. WHEN TO USE: Call extract_shopify_store_intel when your task requires deterministic shopify-intel analysis for store_url; use get_agent_wallet_status to check your remaining free trial quota or prepaid balance. WHEN NOT TO USE: Do not use for unrelated domains or binary media. PARAMETER INTERACTIONS: Pass the target store_url as a non-empty string; omit agent_id and tx_hash during your 5 free trial calls, or supply agent_id (agd_pass_...) / tx_hash for paid execution. Read-only and idempotent; results are cached for 1 hour (<5ms cache hit). $0.01 per call. Pricing: the first 5 calls per agent_id are free and failed calls are never charged. After 5 calls, the tool returns a payment-required quote (not a fatal error) with a $2 Stripe top-up link and Base/Solana USDC addresses; complete payment, then retry with your agd_pass_ key in agent_id or pass tx_hash. Example: extract_shopify_store_intel(store_url='example')
| Name | Required | Description | Default |
|---|---|---|---|
| tx_hash | No | Optional on-chain Base Mainnet (0x...) or Solana SPL USDC transaction hash. Omit unless settling an individual call directly on-chain instead of using an agd_pass_ key in agent_id. | |
| agent_id | No | Optional agent identifier or prepaid agd_pass_ session key. Omit during your 5 free trial calls to use an ID automatically derived from your client IP, or pass your agd_pass_ key after topping up. | |
| store_url | Yes | Target Shopify or e-commerce store URL to extract structured product and pricing intelligence. |
| Name | Required | Description |
|---|---|---|
| data | No | Structured tool output payload. |
| status | Yes | Execution status ('ok' or 'payment_required'). |
| roi_proof | No | Token compression and cost-savings verification metrics. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes well beyond annotations (readOnly/idempotent/openWorld) by disclosing 1-hour result caching (<5ms cache hits), $0.01/call pricing, five free calls per agent_id, that failed calls are never charged, and that quota exhaustion returns a payment-required quote rather than a fatal error. These are exactly the operational traits an agent needs before calling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded and clearly sectioned (WHEN TO USE, WHEN NOT TO USE, PARAMETER INTERACTIONS), but the free-trial and payment mechanics are restated twice ('first 5 calls per agent_id are free' and again in the pricing sentence), padding an already long block.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, return values need not be explained, and the description covers scope, exclusions, parameter interactions, cost, caching, and failure behavior. Nothing an agent needs to invoke it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so the schema already carries the per-parameter definitions, but the description adds the interaction rule: omit both agent_id and tx_hash during free trials, or supply the agd_pass_ key / tx_hash for paid execution. That usage-level interplay is genuinely additive beyond the schema wording.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Extracts live product catalogs, pricing tiers, SKU variants, and stock availability from any Shopify or e-commerce storefront'), immediately distinguishing it from the sibling get_agent_wallet_status. An agent knows exactly what data it gets back 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.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit WHEN TO USE / WHEN NOT TO USE sections, names the alternative sibling (get_agent_wallet_status) for quota checks, and rules out unrelated domains and binary media. This is the full when/when-not/alternative triad.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Inspect an agent's account ledger: remaining free trial calls (out of 5), prepaid USD balance, cumulative spend, total API calls, and total LLM tokens saved. WHEN TO USE: Call before a batch of paid tool executions or after completing a Stripe or USDC top-up to confirm your balance. WHEN NOT TO USE: Do not use to process web content, execute marketplace tools, or submit payments; use the other tools on this server for execution. PARAMETER INTERACTIONS: Omit agent_id to inspect the default trial account derived from your client IP, or pass your explicit agent_id or agd_pass_ session key to check a specific funded wallet. Free and read-only: never charges a fee or consumes a free trial call. Example: get_agent_wallet_status(agent_id='example')
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | No | Optional Agent ID or agd_pass_ session key to inspect. Omit to check the default wallet derived from your client IP. |
| Name | Required | Description |
|---|---|---|
| data | No | Structured tool output payload. |
| status | Yes | Execution status ('ok' or 'payment_required'). |
| roi_proof | No | Token compression and cost-savings verification metrics. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds real context beyond that: it never charges a fee or consumes a free trial call, and the default wallet is derived from the caller's client IP. It does not discuss rate limits or caching, but the cost/free-trial guarantee is meaningful behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the ledger contents, then structured WHEN TO USE / WHEN NOT TO USE / PARAMETER INTERACTIONS / Example. The labeled sections make it scannable, though the repetition of the read-only guarantee and the worked example add a little bulk.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return-value detail is optional, yet the description still names the key fields. With a single optional parameter, no nested objects, and annotations covering safety, an agent has everything needed to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description goes slightly further by naming the agd_pass_ session-key form and framing the two modes as an interaction (omit for IP-derived trial account vs. pass explicit agent_id/session key for a funded wallet), which aids selection even though the schema states the omit behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (inspect) and resource (agent's account ledger) and enumerates exactly what is returned: trial calls out of 5, prepaid USD balance, cumulative spend, total API calls, tokens saved. This clearly separates it from the sibling web-content tools (distill_webpage, extract_structured_data, recon_webpage_skeleton), which operate on webpages rather than wallet state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit WHEN TO USE (before paid tool batches, after a Stripe or USDC top-up) and WHEN NOT TO USE (not for processing web content, executing marketplace tools, or submitting payments). The exclusion clause routes the agent back to the other server tools for execution, so the alternative is named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
extract_shopify_store_intelget_agent_wallet_statusExtracts live product catalogs, pricing tiers, SKU variants, and stock availability from any Shopi
Extracts normalized product catalogs, live prices, variants, and availability from online stores.
Extracts normalized product catalogs, live prices, variants, and availability from online stores.
The public product catalogue and collections of any Shopify storefront, as structured JSON.
Add one secure layer between your agents and this server.
