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pitch_ab_stats

Compare short and full freelance pitches by A/B win rates to identify which format converts more leads into replies or paid work.

Instructions

A/B win rates for short vs full pitches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden, and it discloses nothing beyond the metric itself — no data window, no sample-size or minimum-volume caveats, no indication of what counts as a 'short' vs 'full' pitch, and no statement of read-only/non-mutating behavior.

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?

A single front-loaded clause with no filler. Nothing can be trimmed without losing the metric definition.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and zero parameters keeps the surface small. However, with no annotations and no usage or behavioral context, the definition is only minimally viable — it never says what a 'short' or 'full' pitch means or over what period the win rates are computed.

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 tool takes zero parameters, so per the rubric the baseline is 4; the description reasonably implies the comparison dimension (pitch length) is baked in rather than parameterized.

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

Purpose4/5

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

States a specific metric and scope: win rates comparing short vs full pitches. The agent can infer this returns an A/B comparison statistic, though no verb (returns/computes/compares) is given and no sibling is named for differentiation — none of the listed siblings are obviously confusable, so the gap is modest.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no trigger conditions, and no mention of alternatives. The agent must guess whether this is a reporting tool to run proactively, a diagnostic to run after a batch of pitches, or something gated on prior activity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.