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quantumproxies

quantumproxies-mcp

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save_parser_preset

Save a parser preset to reuse by ID, and enable self-healing regeneration when site structure changes. Provide a source URL to allow it to relearn and bump version automatically.

Instructions

Store a generated parser under a name so it can be reused by id. Scrape later with scrape's preset_id instead of repeating the selectors, and every run is scored per field — when the recent success rate decays (the site redesigned), the preset regenerates itself from source_url and bumps a version. Give it a source_url whenever you can: without one it can never self-heal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesA name you'll recognise, e.g. 'amazon product page'
fieldsNoThe original field descriptions, so a self-heal regenerates the same shape
parserYesThe parser to store — normally the `parser` object returned by generate_parser
renderNoThe page needs a browser render to show its content
auto_healNoRegenerate automatically on decay (default true when source_url is set)
source_urlNoPage to relearn from when the parser decays — required for self-healing
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that every run is scored per field and that the preset regenerates itself on decay, bumping a version. It also transparently notes that without a source_url it can never self-heal. This adds significant behavioral context beyond the schema. It does not mention permissions or side effects like name conflicts, but the core behavior is well conveyed.

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 sentences with no fluff. The first sentence states the primary purpose, the second explains reuse, scoring, and self-healing, and the third gives a best-practice recommendation. Information is front-loaded and every sentence earns its place.

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?

For a tool with 6 parameters, nested objects, and no output schema, the description covers the primary use case, the self-healing behavior, and the critical dependency on source_url. It doesn't explain return values or edge cases like name conflicts, but the essential information for correct selection and invocation is present. Given the complexity, it is reasonably complete, though more detail about the return value and overwrite behavior could push it to 5.

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?

Schema description coverage is 100%, so baseline is 3. The description adds little beyond the schema; it reiterates the self-healing requirement of source_url but doesn't elaborate on parameters like `fields` or `auto_heal`. It mentions `preset_id` but that is not a parameter of this tool. No additional parameter meaning is provided, so a score of 3 is appropriate.

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 a specific verb ('Store'), a specific resource ('a generated parser'), and its purpose ('so it can be reused by id'). It also distinguishes itself from siblings by referencing scrape's `preset_id` and self-healing behavior, making it distinct from generate_parser and list_parser_presets.

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?

It explains the usage context: save a parser for later reuse via scrape's `preset_id`, and advises to provide a `source_url` for self-healing. It doesn't explicitly state when not to use it or alternative tools, but the context of generating a parser first and then saving is implied. The instruction 'Give it a source_url whenever you can' is a clear guideline. No explicit exclusions or alternatives are named, but the purpose is direct.

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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