Free live scan: this month's Reddit threads where people are complaining about a named product, asking for alternatives, or evaluating it. Classified by complaint-shaped language with the threads as receipts. Limited to 5 scans per day.
| Name | Required | Description | Default |
|---|---|---|---|
| competitor | Yes | The product or company name, e.g. "HeyReach". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
It discloses the rate limit ('Limited to 5 scans per day') and explains the classification heuristic ('complaint-shaped language with the threads as receipts'), giving insight into how results are produced. No annotations exist, so this is valuable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences deliver the core purpose, methodology, and limit with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the scan's temporal scope, classification approach, and rate limit; it lacks explicit output format details, but the mention of 'threads as receipts' suggests the result includes thread references.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'competitor' is fully described in the schema; the description adds no further semantic detail about the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'live scan' of 'this month's Reddit threads' where people 'complain', 'ask for alternatives', or 'evaluate' a named product, which distinguishes it from sibling tools like find_buyer_threads or demand_radar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context that this tool is for surfacing complaints and alternative-seeking discussions about competitors, but it does not explicitly contrast with sibling tools or state when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a clearly distinct function: find_buyer_threads starts a search, get_demo_report retrieves results, reddit_demand_board shows trends, subreddit_rules provides policy info, and get_started offers guidance. The related pair of find/get is complementary rather than overlapping, so an agent would not mix them up.
Tool names follow a loose verb_noun pattern for find_buyer_threads, get_demo_report, and get_started, but reddit_demand_board and subreddit_rules are noun phrases. This mixed style is readable but not fully consistent with a single convention.
With 5 tools, the server is well-scoped for its purpose of Reddit demand research and community vetting. Each tool covers a distinct aspect without unnecessary bloat, making it easy for an agent to navigate.
The tool set covers the full workflow: initiating a buyer-thread search, fetching the report, exploring broader demand trends, checking subreddit rules, and getting started. No critical operations are missing for the advertised functionality.