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Route a founder's dilemma to the debates that genuinely bear on it. Present the readings SEPARATELY — never merge them into one answer. Respect the question's altitude: scale-up material does not answer a pre-PMF dilemma. When coverage is thin it says so — advise from general knowledge rather than stretching a weak match. Returns ≤4 debates and ≤36 stances — a sample, not the full set; get_stances(debate_id) has a debate's complete stances, each with speaker, date, strength and a receipt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesThe founder's question or dilemma, with a line of context

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds substantial behavior an agent could not infer: bounded output (≤4 debates, ≤36 stances), never merging readings, respecting question altitude, and admitting thin coverage before falling back to general knowledge. This far exceeds the safety profile already carried by the 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?

Roughly 90 words, front-loaded with the core routing purpose, then behavioral constraints, output bounds, and sibling pointer in logical order. Every sentence carries a distinct job — presentation rule, altitude rule, coverage honesty, sample limits, and the get_stances handoff — with no filler.

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?

With no output schema, the description carries the full burden of explaining returns, and it does so via explicit bounds (≤4 debates, ≤36 stances) and sample semantics, then routes to get_stances for complete data with its constituent fields (speaker, date, strength, receipt). An agent has everything needed to invoke this tool correctly, interpret its output, and escalate when necessary.

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 coverage is 100%, so the baseline is 3 — the schema already defines 'topic' as the founder's question with a line of context. The description weakly reinforces this by adding the altitude constraint on what makes a legitimate topic, but it supplies no extra syntax, formatting, or example guidance beyond the schema.

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 action ('Route a founder's dilemma') and resource ('the debates that genuinely bear on it'), immediately establishing what the tool does. It also distinguishes itself from the get_stances sibling by calling its own output 'a sample, not the full set,' so an agent can't confuse the two.

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?

Gives clear context on when to rely on this tool (matching a dilemma to relevant debates) and explicitly names get_stances(debate_id) as the route to complete stances for a debate. The altitude and thin-coverage rules add behavioral do's and don'ts, but there is no explicit exclusion of list_debates, get_context, or trace_evolution, leaving some sibling differentiation to inference.

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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