Fetch the results of a find_buyer_threads run: top matched buyer threads with relevance scores, plus a link to the full report with reply drafts.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The run slug returned by find_buyer_threads. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It accurately describes the read-only fetch behavior and provides specifics about the returned data (relevance scores, link to report). While it does not mention error handling or side effects, the fetch verb and output details give a transparent picture.
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?
The description is a single, front-loaded sentence that states the action and the key output components. Every word earns its place with no filler or repetition.
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?
For a simple one-parameter retrieval tool with no output schema, the description is complete. It explains what the parameter is, where it comes from, and what the result contains, covering all needed context for correct usage.
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?
Schema coverage for the parameter is 100% (slug described as 'The run slug returned by find_buyer_threads.'). The description adds minimal extra meaning beyond the schema, only reinforcing that the slug comes from a prior run, which is already in the schema description. Baseline 3 applies.
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 the tool's function: fetching results from a find_buyer_threads run. It specifies the resource (run results) and the content (top matched threads, relevance scores, link to full report), distinguishing it from sibling tools like find_buyer_threads itself.
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?
The description implies the tool is used after find_buyer_threads by mentioning 'a find_buyer_threads run' and 'run slug returned by find_buyer_threads'. This provides clear context for when to use it, though it does not explicitly state when not to use it or name alternatives.
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.
Several tools (competitor_complaints, demand_radar, reddit_demand_board, find_buyer_threads) all mine Reddit threads for demand, complaints, or buyer interest, with overlapping purposes that could easily confuse an agent. The boundaries are unclear, especially between demand_radar and reddit_demand_board, which both offer weekly demand overviews.
All names use snake_case and are readable, but the pattern is mixed: some are verb-first (find_buyer_threads, get_demo_report, get_started) while others are noun-heavy phrases (competitor_complaints, reddit_demand_board, subreddit_rules). This inconsistency makes the set feel less predictable.
With 7 tools, the set is well-scoped for a focused Reddit market research server. Each tool serves a distinct function within the domain, and none feel redundant or excessive.
The tool set covers the core workflows: discovering demand, finding buyer threads, checking competitor complaints, and understanding community rules. Minor gaps include lack of direct keyword search or alerting, but agents can chain existing tools to achieve most goals.