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Judge a startup idea

judge_idea

Judge a startup or side-project idea. Returns a verdict (verdict KILL, FIX or SHIP, shown as verdict_label KILL IT, FIX IT or SHIP IT), an overall score, the best_signal, the biggest_risk and the eight scored dimensions. If the idea is too vague to judge, needs_detail is true and verdict, verdict_label, score, best_signal and biggest_risk are null, and message says which details are missing. 10 Jev decisions in about a second. Deterministic rubric, no generated prose. The text result is a preformatted card with bar charts.

Input Schema

NameRequiredDescriptionDefault
goalNoWhy the idea is being built, which decides the questions it is scored on. Making money judges it as a business. Open source scores Adoption instead of Money. Just for fun scores Immediate appeal and Fun instead of Real problem and Money.money
ideaYesThe idea in plain words: who it is for, what it does, how it makes money or spreads. More detail, better verdict.
do_not_archiveNoWhen true, the idea text is not stored, for confidential ideas. Otherwise it is archived anonymously (no IP, no identity).

Output Schema

NameRequiredDescriptionDefault
goalYesThe goal the idea was judged against.
scoreYesOverall score: weighted average of the dimension scores, rounded. null when needs_detail is true.
try_itYesLink to the Kill My Idea website.
messageYesOne-line summary such as "SHIP IT. 72/100.", or the request for more detail when needs_detail is true.
verdictYesVerdict code from the score and the thresholds below. null when needs_detail is true.
categoryYesProduct category Jev assigned to the idea.
judged_byYesThe model that judged the idea.
dimensionsYesThe scored questions for this goal, in display order.
latency_msYesTime Jev took to answer, in milliseconds.
thresholdsYesScore ranges for each verdict.
best_signalYesThe highest-scoring dimension. null when needs_detail is true.
biggest_riskYesThe lowest-scoring dimension. null when needs_detail is true.
needs_detailYesTrue when Jev could not understand the idea well enough to judge it: no verdict, score or signals are given, and message says which details are missing.
verdict_labelYesDisplay form of the verdict, e.g. "KILL IT". null when needs_detail is true.
scoring_versionYesVersion of the questions, weights and thresholds used.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true and non-idempotence, so the safety bar is lower; the description still adds real context beyond them — deterministic rubric, no generated prose, roughly one-second latency, and the exact null-field contract when needs_detail is true. The main deduction is the cryptic '10 Jev decisions in about a second', which adds noise more than information.

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

Conciseness4/5

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

Front-loaded with the purpose, then the success shape, then the failure shape — a sensible order. The nested parentheticals (e.g. 'KILL, FIX or SHIP, shown as verdict_label KILL IT, FIX IT or SHIP IT' and '10 Jev decisions') make it denser than it needs to be.

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?

For a single-call judging tool with three simple parameters, an output schema and full annotation coverage, the description covers purpose, both return paths, determinism and latency. Nothing an agent needs in order to invoke it correctly or interpret the result is missing.

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 goal, idea and do_not_archive are already fully documented in the schema, including the enum's scoring consequences. The description text itself says nothing about parameters, so it sits at the baseline rather than adding meaning.

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?

States a specific verb and resource ('Judge a startup or side-project idea') and immediately enumerates the exact outputs (verdict KILL/FIX/SHIP, overall score, best_signal, biggest_risk, eight scored dimensions). The only sibling, get_stats, is obviously a different concern, so an agent can route without opening the schema.

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

Usage Guidelines3/5

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

Usage is implied by the purpose rather than stated: nothing says when to prefer this over get_stats or when an idea is out of scope. The one piece of conditional guidance given is behavioral ('If the idea is too vague to judge, needs_detail is true...'), which tells the agent what a rejected input looks like but not when to call the tool.

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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