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sch_set_components_parameters

Bulk-update parameters on placed schematic components in one undo group to avoid slow per-component loops. Use after audits flag parameter bugs like wrong supplier PN or placeholders.

Instructions

Bulk-update parameters on PLACED schematic components.

Single IPC call wraps N component updates inside one PreProcess/PostProcess undo group. Avoids the 10-100x slowdown of looping the singular variant. The canonical follow-up tool after audits that flag parameter-level bugs -- audit_find_visible_supplier_pn, audit_find_placeholder_values, audit_find_mpn_inconsistencies -- recommend it.

Each stamp targets one component by designator and sets one or more parameters. Special keys allowed:

  • Value, Comment, Manufacturer, MPN, Footprint, Description, HelpURL, etc.

  • Custom parameters: any key name. Unknown parameters are CREATED if they don't already exist on the component.

Args: stamps: List of dicts. Each dict must include designator and one or more parameter key/value pairs. Example: [{"designator": "R1", "Value": "10k", "Manufacturer": "Yageo", "MPN": "RC0603FR-0710KL"}, {"designator": "C5", "Value": "100nF"}] sheet_path: Optional explicit SchDoc path. Empty uses the currently-focused schematic.

Returns: Dict with {updated, failed, total}. updated is the count of components whose parameters were touched; failed is the count of stamps that couldn't be applied (designator not found, parameter not settable, etc). A Footprint key repoints the part's footprint model; footprints_applied counts the ones that read back the new name and footprints_not_applied lists designators whose part has no footprint model or did not take it.

Input Schema

NameRequiredDescriptionDefault
stampsYes
sheet_pathNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.1

TDQS

A4.6/5.0
Behavior4/5

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

No annotations exist, so the description carries the full load, and it does well: single IPC call, one PreProcess/PostProcess undo group, unknown parameters are CREATED, and a Footprint key repoints the footprint model with read-back verification. It stops short of stating permission requirements or whether partial failures leave the document in a half-updated state, which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose and the sibling-routing rule; the Args/Returns blocks earn their space given 0% schema coverage. It is slightly long with some conversational padding ('recommend it', 'etc.'), but nothing critical is buried.

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 mutation tool with zero annotations, the definition covers return shape (updated/failed/total plus footprint counters), creation semantics, and failure counting. An output schema exists so return values are doubly covered; remaining gaps (atomicity on partial failure, auth) are minor but real.

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 coverage is 0%, but the description fully compensates: it explains that stamps is a list of dicts each requiring a designator plus one or more key/value pairs, gives a concrete JSON example, lists special keys (Value, Comment, Manufacturer, MPN, Footprint, Description, HelpURL), and describes custom-key creation behavior. sheet_path's default/empty behavior is also spelled out.

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?

States a specific verb and resource ('Bulk-update parameters on PLACED schematic components') and immediately distinguishes itself from the singular variant it wraps. An agent can tell it apart from library-side batch tools like lib_batch_set_params because the target (placed schematic components) is named explicitly.

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?

Explicitly says when to use it (canonical follow-up after parameter audits), names the three audit tools that flag such bugs, and explains why not to loop the singular variant (10-100x slowdown). This is the exact when/why/alternative routing an agent needs.

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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