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request_revalidation

Request a fresh validation run for an idea after a significant pivot or update, re-running the AI agents to produce an updated VC score. Optionally target specific agents instead of the full suite. This spends credits and starts background work; not read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentsNoSpecific agents to re-run. Omit for full re-validation.
ideaIdYesThe idea ID
reasonNoWhy is re-validation needed?

Output Schema

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

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already set readOnlyHint=false, idempotentHint=false, and destructiveHint=false. The description adds critical behavioral context beyond these annotations: 'This spends credits and starts background work; not read-only.' This informs the agent of non-idempotent, credit-costly, asynchronous behavior that the annotations alone do not fully convey. No contradiction with annotations.

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?

Three sentences, each earning its place: the first states the core purpose and trigger, the second provides an optional usage variant, and the third covers critical behavioral side effects. No wasted words.

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

Completeness5/5

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

Given the tool has only 3 parameters (all documented in schema), has a high schema coverage, and has no nested objects, the description is complete. It covers the trigger, optional parameter usage, and side effects (credit cost, background work, non-read-only). With an output schema present, the description does not need to detail return values.

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?

Schema description coverage is 100%, so baseline is 3. The description adds value by clarifying the meaning of the 'agents' parameter ('Optionally target specific agents instead of the full suite'), but the 'ideaId' and 'reason' parameters are adequately described in the schema. The description does not add significant new semantics beyond the schema, so 3 is appropriate.

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 requests a 'fresh validation run for an idea after a significant pivot or update', specifying the verb ('request'), resource ('validation run'), and context ('after a pivot or update'). It also distinguishes itself from the sibling 'validate_my_idea' by mentioning an optionally targeted set of agents and the production of a 'VC score', which is unique among siblings.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('after a significant pivot or update') and what it does ('re-running the AI agents'). It also provides an important usage alternative: 'Optionally target specific agents instead of the full suite.' Behavioral cautions ('spends credits and starts background work; not read-only') further guide appropriate use.

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