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Read code updates

get_code_updates
Read-onlyIdempotent

Knowledge base → Code updates for a hosted product: who writes the updates, whether they publish by themselves, each repository, and the latest checks with the article updates waiting for review. Pass batchId to read one check's proposals in full.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many checks, 1-50. Defaults to 10.
batchIdNoOne check, with each proposal in full.
productIdYesProduct id from list_products.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful behavior context — that batchId switches from a per-check summary to full proposals, and that the default view surfaces only article updates awaiting review — but says nothing about pagination, result ordering, or the shape of the returned data.

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?

Two sentences, front-loaded with the domain context and following with the batchId drill-down instruction; little wasted text. The 'Knowledge base → Code updates' arrow notation is slightly cryptic but compact, and the first sentence is dense with an embedded list.

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?

With no output schema, the description does the heavy lifting of telling the agent what the response contains (writers, publishing mode, repositories, latest checks, pending article updates), which is the key gap a read tool leaves. It is still thin on pagination/limit interaction and how productId scopes the result, keeping it short of a 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 the schema already documents productId, limit, and batchId, making 3 the baseline. The description only elaborates on batchId (matching the schema's own wording) and says nothing about productId or the meaning of limit beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description enumerates the domain object well (code updates for a hosted product: writers, self-publishing, repositories, checks awaiting review), so the resource is identifiable, but it never states a clean action verb — it reads more like an output summary than 'retrieve/list code updates'. It also does not explicitly contrast itself with the mutate/sibling tools (edit_code_update, approve_code_update, discard_code_update).

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

Usage Guidelines3/5

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

'Pass batchId to read one check's proposals in full' gives one concrete conditional usage hint for expanding a check. Beyond that there is no when-to-use guidance: no statement that this is the read entry point for a product, no mention of when to reach for it versus list_products or the edit/approve siblings.

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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