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gabrielbelli

pelando-mcp

by gabrielbelli

get_deal_comments

Read a deal's full comment thread to see crowd corrections and warnings about fake discounts or bad postings, since Pelando has no flag field. Limit truncates the tree locally.

Instructions

Read a deal's comment thread — where the crowd corrects a bad posting.

The thread is the only place a fake discount gets explained; there is no report or flag field in Pelando's data. Note the upstream endpoint has no pagination and returns the whole tree at once, so limit truncates locally and truncated tells you when that happened.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
id_or_slugYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.1

TDQS

B3.4/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and discloses important behavior: the upstream endpoint has no pagination, returns the whole tree at once, and the local limit truncates results. It also mentions a truncated indicator, which helps the agent interpret output, though it omits auth, rate limits, and broader return structure.

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 appropriately sized and front-loads the purpose in the first clause. The second sentence adds useful context about why the thread matters, and the third covers pagination behavior without excessive padding.

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

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description should do more, but it does cover the critical non-pagination behavior and truncated output signal. It still leaves the return shape, comment structure, and identifier format largely to inference.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for both parameters. It explains limit well—local truncation rather than server-side pagination—but gives no explicit semantics for the required id_or_slug parameter beyond the general phrase 'a deal's comment thread.'

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 clearly states the verb and resource: 'Read a deal's comment thread.' It distinguishes the tool from generic deal-fetching siblings by focusing on the comment thread and its role in correcting bad postings, though it does not explicitly name sibling alternatives.

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?

Usage is implied rather than explicit: the thread is framed as the place to investigate fake discounts and corrections because no report/flag field exists. However, the description gives no direct when-to-use instruction or comparison against tools like get_deal or assess_deal_quality.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.