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log_build_progress

Log a build event for an idea to keep its build timeline up to date (commits, deploys, milestones and more). Valid events: build_started, commit_pushed, deploy_started, deploy_completed, test_passed, test_failed, milestone_reached, error_encountered, commit, deploy, milestone, ci_pass, ci_fail, pr_merged, first_deploy, mvp_complete, launch. Not read-only; each call appends a new event, so it is not idempotent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventYesBuild event type
ideaIdYesThe idea ID
messageNoFree-form message
metadataNoArbitrary metadata
builderIdNoBuilder ID
deployUrlNoDeployment URL
commitCountNoNumber of commits

Output Schema

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

TDQS

A4.4/5.0
Behavior4/5

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

The description explicitly states it is 'not read-only' and 'not idempotent', and that 'each call appends a new event'. This aligns with annotations (readOnlyHint: false, idempotentHint: false) and adds behavioral context beyond the annotations, such as the non-idempotent appending behavior. There is 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?

The description is three sentences, clearly front-loaded with the primary purpose. The first sentence immediately states what the tool does and its context, followed by a list of events and a warning about behavior. Every sentence is essential and adds value, 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 the tool has 7 parameters (2 required), an output schema (not shown but indicated), and annotations covering read-only and idempotence, the description is reasonably complete. It explains the tool's effect on the idea's timeline, lists events, and warns about non-idempotence. A minor gap is not specifying how the event affects the timeline or what the response looks like, but the presence of an output schema likely addresses return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides full (100%) descriptions for all 7 parameters, so the baseline is 3. The description adds value by listing all valid event values inline (though also present in the schema), and by framing the purpose of the parameters ('log a build event', 'keep timeline up to date'). However, it does not explain the 'message' or 'metadata' parameters beyond what the schema provides.

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 verb ('Log') and the resource ('build event for an idea'), and explains the purpose ('keep its build timeline up to date'). It lists valid event types, which helps the agent understand the scope. This differentiates it from siblings like 'update_idea' or 'update_idea_status' which focus on different aspects.

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 explicitly states it is 'not read-only' and 'not idempotent', which guides against misuse. It does not provide explicit when-not-to-use guidance or mention alternative tools among the many siblings, but the context of appending events to a timeline is clear and sufficient for most use cases.

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