Thread Otter

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.

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

With no annotations, the description carries the full burden. It discloses the output type (comparison, top themes, thread receipts) and optional param behavior, but does not mention side effects, authentication, rate limits, or data freshness. Adequate but not deep.

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?

Two sentences pack the core purpose, category list, and usage instructions without redundancy. Front-loaded and efficient.

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 tool with one optional parameter and no output schema, the description covers purpose, usage, and output summary sufficiently. Lacks edge-case handling or exact response format, but is largely complete.

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 schema already documents the parameter and valid values (100% coverage). The description adds meaning by explaining how the parameter changes the output (comparison vs. detail), which goes beyond the schema.

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 performs a 'weekly comparison of buyer demand on Reddit' and enumerates the specific categories. It distinguishes itself from sibling tools by emphasizing the aggregated, weekly overview nature.

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?

Provides explicit call patterns ('Call with no arguments for the comparison, or pass a category key for its detail'), but does not name alternative tools or exclusion criteria. Context is clear, so it earns a 4 rather than 3.

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

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

With no annotations provided, the description carries the full burden. It transparently discloses the multi-step process (crawl, buyer identification, Reddit mining), the async nature (results ready in ~2-3 minutes via get_demo_report), and a rate limit (2 runs/day). This is comprehensive for a demo tool, covering both behavior and constraints.

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 three sentences, each earning its place: the first explains the core function, the second covers output and timing, and the third states the limitation. No fluff, front-loaded with the most important context (free GTM demo) and easy to parse.

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?

Despite having no output schema, the description explains what the return looks like (report link) and how to get results (via get_demo_report). It also conveys the tool's role within a broader workflow (GTM demo) and mentions the rate limit, making it complete for the tool's complexity and context.

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 input schema has 100% coverage for both parameters (website_url and email), with clear descriptions. The tool description reinforces the website_url role ('give it a product website URL') but does not add substantial new semantics beyond the schema. Baseline 3 is appropriate given the high schema coverage and marginal added value.

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: provide a product website URL, Thread Otter crawls the site, identifies buyer personas, and mines relevant Reddit threads. It uses specific verbs ('crawls', 'mines') and the resource (Reddit threads, website URL), which distinguishes it from sibling tools like get_demo_report (retrieval) and reddit_demand_board (likely similar but not same workflow).

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 frames this as a 'free GTM demo' and gives a clear workflow: call this tool, then use get_demo_report after 2-3 minutes. It also notes the 2-runs-per-day limit, which sets usage expectations. However, it doesn't explicitly contrast with alternatives like reddit_demand_board or subreddit_rules, so it falls just short of full guidance.

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

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.

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool works without authentication and outlines the specific topics it covers. This gives the agent a good understanding of what to expect, though it doesn't explicitly describe the output format (e.g., text, markdown).

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 sentence that is front-loaded with the main purpose ('How to connect Thread Otter') and efficiently lists the covered topics. It avoids unnecessary words and is well-structured for a quick understanding.

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?

Given that the tool has no params, no output schema, and no annotations, the description is quite complete for a simple informational tool. It covers the main purpose, content areas, and authentication requirement. A minor gap is the lack of explicit return format, but this is not critical for an onboarding guide.

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 tool has zero parameters, and the input schema is empty. The description doesn't need to explain parameters, and the baseline for 0-param tools is 4. The description adds context about the tool's purpose without confusing parameter details.

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 purpose: it explains how to connect to Thread Otter, covering server purpose, free tools, trial signup, and API setup. This distinguishes it from sibling tools that focus on data queries (e.g., find_buyer_threads, get_demo_report), making it unmistakably an onboarding guide.

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 use when the user is new to the server or needs connection/setup information. It explicitly notes 'Works without authentication,' which is a clear guideline for when this tool can be used. While it doesn't name alternatives, its unique role among siblings is apparent from the content.

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

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

No annotations are provided, so the description carries the full burden. It discloses the read-only nature implicitly (a 'board' of information), the weekly update cadence, and the inclusion of thread links. However, it doesn't mention potential errors, rate limits, or explicit side-effect safety, leaving some gaps.

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 two sentences, front-loaded with the core value proposition and then clear invocation options. Every sentence earns its place with no redundancy or 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?

For a tool with one optional parameter and no output schema, the description covers what it returns, how to invoke it, and the data scope. It could specify the output structure more, but it's sufficient for an agent to decide and call correctly.

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 input schema already describes the community parameter, but the description adds the critical no-argument behavior (cross-community leaderboard) and clarifies that passing a community yields its full breakdown. This goes beyond the schema's per-community description.

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 provides a weekly board of demand signals (recurring pains, missing tools, paying-shaped demand) across 40 subreddits, with real thread links. It distinguishes from sibling tools by emphasizing cross-community aggregation and optional per-community breakdown.

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 gives clear invocation guidance: call with no arguments for the cross-community leaderboard, or pass a community for its full breakdown. It doesn't explicitly contrast with sibling tools, but the use case is obvious and the context is sufficient.

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

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

With no annotations, the description carries the transparency burden. It discloses the data source (Thread Otter's vetting data, 2,000+ subreddits), that it is free, and the kind of content returned. However, it does not mention what happens for unprofiled subreddits or potential data staleness, leaving some edge cases undocumented.

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, economical sentence with a clear lead-in ('Free lookup') followed by a colon and specific output types. Every phrase earns its place, and there is no verbose repetition of schema information.

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 lookup tool without an output schema, the description sufficiently explains what the tool does and what it returns. It covers the key output categories (self-promo, link policy, writing style) but does not specify behavior for missing or niche subreddits. Overall, it is complete enough for the tool's simplicity.

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 input schema already fully documents the single parameter 'subreddit' with an example. The description adds no additional parameter-specific semantics beyond what the schema provides. Baseline 3 is appropriate since schema coverage is 100%.

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 a specific action ('lookup') and a specific resource ('a subreddit's promotion posture'), and enumerates what it returns (self-promo policy, link policy, how to write for the room). This distinguishes it from sibling tools like find_buyer_threads or get_demo_report, which serve different purposes.

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 communicates a clear use case: quickly look up a subreddit's rules before posting. It does not explicitly mention alternatives or when not to use it, but the sibling tools are distinct enough that the intended context is clear. It provides context (free lookup, data source) but lacks exclusion guidance.

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