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run_arena_duel

Start an Arena Duel that pits your idea head-to-head against a competitor idea for an AI-judged comparison, returning a session ID you can poll for the result. This spends credits and starts an async job. Not read-only; pass your ideaId and the opponent ideaId, and check credits first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ideaIdYesYour idea ID
languageNoResponse languageen
opponentIdeaIdYesThe competitor idea ID to duel against

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesThe tool result rendered as human and AI readable text or markdown.

TDQS

A4.4/5.0
Behavior5/5

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

The description adds significant behavioral detail beyond the annotations: it clarifies that the tool spends credits, runs as an async job, and returns a session ID for polling. This goes beyond the readOnlyHint=false annotation and provides crucial transparency about side effects and workflow, with no contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences totaling about 30 words. The first sentence fronts the core purpose and return value; the second adds critical usage notes. Every sentence serves a clear purpose with no redundancy.

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?

Given that the tool has an output schema and annotations, the description covers the main behavioral aspects: async polling, credit cost, and required parameters. It does not detail error cases or the polling endpoint, but the presence of an output schema likely covers return structure, making this fairly complete for an agent.

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?

All three parameters are described in the schema with 100% coverage, earning a baseline of 3. The tool description merely echoes the parameter names (ideaId, opponentIdeaId) without adding new semantic value, such as format constraints or usage tips for the optional language parameter.

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

Purpose5/5

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

The description clearly states the tool's purpose: starting an Arena Duel that compares two ideas using AI, returning a session ID. It uses specific verbs (start, pits) and resources (arena duel, idea, competitor idea), effectively distinguishing it from sibling tools like run_survival_mode or run_time_machine.

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

Usage Guidelines4/5

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

The description provides explicit usage context: it spends credits, is asynchronous, requires checking credits first, and is not read-only. However, it does not explicitly state when not to use it or mention alternative tools, so it is slightly lacking in exclusion guidance.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct function or data aspect, from idea CRUD to simulations, content generation, and team management. Despite the large number, descriptions clearly differentiate purposes, e.g., 'get_idea_summary' vs. 'get_idea_agents' vs. 'get_idea_evolution'. No two tools appear to do the same thing.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (e.g., 'create_idea', 'get_competitive_density', 'toggle_favorite'). No mixing of conventions like camelCase or abbreviations. The pattern is uniform and predictable.

Tool Count2/5

63 tools is far beyond the typical well-scoped range of 3-15. While the platform's broad scope (idea validation, B2B, team, simulations) justifies many, the sheer volume can overwhelm an agent. A more curated subset or grouping would improve coherence.

Completeness5/5

The tool set covers the full startup idea lifecycle: creation, validation, retrieval of various analyses, updates, deletion, sharing, simulations, B2B lead generation, team collaboration, and market intelligence. No obvious gaps exist for the stated domain.

Resources