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Decian-Inc

connectsecure-mcp

by Decian-Inc

patch_w_company_companies

Update company records via PATCH to /w/company/companies. Provide route IDs, filters, headers, and payload to modify existing company data.

Instructions

Update company Calls PATCH /w/company/companies. Provide route IDs in path_params, filters and pagination in query, and any required request headers in headers. Provide the request payload in body.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
queryNo
headersNo
path_paramsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

There are no annotations, so the description must carry the full behavioral burden. It only says 'Update company' and describes parameter locations, but does not mention side effects, idempotency, whether the body is a partial update, required permissions, or what happens to unmentioned fields. 'Update' implies mutation, but the description omits all behavioral specifics.

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?

The description is short (two sentences) and front-loads the core action ('Update company'). The 'Calls PATCH...' phrasing is slightly awkward but not harmful. No filler words or redundant explanation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

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 and no output schema (despite 'Has output schema: true', the schema is not provided in the context), the description is incomplete. It lacks information about the expected result, error conditions, whether it supports partial updates or replaces, and prerequisites like an existing company ID. An agent would not fully understand what the tool does beyond issuing a PATCH request.

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 coverage is 0% (all params are generic objects with no descriptions). The description adds some semantic value by mapping 'route IDs' to path_params, 'filters and pagination' to query, 'required request headers' to headers, and the 'payload' to body. However, it doesn't specify the content of these objects, leaving the actual company fields undocumented. This only partially compensates for the schema gap.

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?

The description states a specific verb ('Update') and resource ('company'), and references the REST method PATCH /w/company/companies. It clearly differentiates from sibling tools like post_w_company_companies (create) and delete_d_company_companies_id (delete), though it doesn't explicitly name them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to choose this tool over alternatives. It only tells where to put parameter components (path_params, query, headers, body). It doesn't mention creating a company with POST, retrieving with GET, or deleting with DELETE, so an AI agent lacks usage context for making the correct selection.

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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