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pricewatcha

by io.github.pricewatcha

Track product

track_product

Submit a public product URL for price tracking. Waits up to ~25s server-side; fast shops return status "completed" with product in one call. Slow jobs return status "running" with job_id — poll get_job_status. On failure, returns a structured error object with fields error.code, error.message, error.http_status, error.retry_recommended, and error.retry_after_seconds.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic product page URL from a supported shop

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hintNo
errorNo
job_idYes
statusYes
productNo

TDQS

A4.7/5.0
Behavior5/5

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

Beyond annotations (which show destructiveHint=false, etc.), the description reveals key behavioral traits: server-side wait time, possible response statuses, the need for polling, and the full error object structure. This is comprehensive and alerts the agent to potential long-running operations.

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?

The description is concise at 4 sentences, each serving a distinct purpose: what the tool does, timing, possible outcomes, and error details. No redundant or unnecessary information.

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?

Given the tool's asynchronous nature, the description is complete: it explains the request-response cycle, how to handle both fast and slow cases, and the error contract. No missing information given that an output schema exists.

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

Parameters3/5

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

The input schema covers 100% of the parameter (url with description), so the description adds no further parameter semantics. It simply restates 'public product URL' without additional format or usage constraints.

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?

The description clearly states the tool's purpose: 'Submit a public product URL for price tracking.' It distinguishes itself from sibling tools like get_job_status by explaining when to use each (e.g., poll get_job_status for slow jobs).

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?

The description provides explicit guidance: it explains the expected behavior (waits up to ~25s), how to handle fast vs. slow responses (immediate completion vs. polling get_job_status), and what to do on failure (structured error object with retry details).

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool clearly maps to a distinct resource and action: price alert CRUD verbs (create/get/list/update/delete) are unambiguous, and get_api_status vs get_job_status are separated by scope (service health vs async job polling). track_product, search_products, get_product, and get_price_history each address a different part of the product workflow with no meaningful overlap.

Naming Consistency5/5

All 11 tools follow a consistent verb_noun snake_case pattern: create_price_alert, get_price_history, track_product, list_price_alerts, and so on. Verbs are precise and nouns are stable across the set, making the API surface predictable.

Tool Count5/5

At 11 tools, the server is well-scoped for its purpose: alert management, product search, price history, tracking, and status checks each earn their place. No tool feels redundant or excessive for a price-intelligence domain.

Completeness4/5

The price alert lifecycle is fully covered with create/get/list/update/delete, and product search/tracking/history are solid. A minor gap is the lack of a way to list or stop all tracked products/jobs besides polling a known job_id, but this can be worked around and core workflows are complete.

Resources