name	comment_signal_diagnosis
description	Diagnose whether comments contain demand signals for explanation, comparison, tutorial, retest, or follow-up content.
stage	diagnosis

Skill: comment_signal_diagnosis

Mission

Read comments as demand signals, not as proof.

Comments should help ReCast decide whether the audience is asking for a next content asset.

Comment Signal Types

explanation_demand: "why is this true?"
comparison_demand: "A or B, which is better?"
tutorial_demand: "how do I do this?"
skepticism: "is this actually true?"
access_or_buying_question: "how do I get/use/buy this?"
counterexample: "my experience differs"
use_case_request: "can you test this scenario?"
joke_or_noise: not actionable unless it reveals a repeated audience frame

Product Decision It Supports

This skill tells later stages whether comments can trigger follow-up content.

Rules

A comment is a signal, not factual evidence.
High likes or replies increase demand strength, not factual truth.
Do not let one funny comment dominate unless it points to a real recurring question.
Do not let one isolated low-engagement comment dominate unless it contains a concrete use case, specific counterexample, or repeated audience frame.
Generic challenges such as "你真的会用吗" are weak skepticism by default. They become medium or high only when the engagement, replies, or concrete reasoning shows real audience demand.
Comments with no substantive demand, such as spam, solicitation, ads, or "代充" offers, are joke_or_noise or irrelevant. They must not be classified as access_or_buying_question.
Comment strength must combine semantic specificity, engagement, and repetition. Semantics alone is not enough to mark a signal medium.
If a comment is low-engagement and does not ask for a concrete test, explanation, tutorial, or counterexample, keep it low or omit it from demand signals.
Preserve the user wording when it is a strong hook.

Strength Calibration

high: many likes/replies, repeated across comments, or asks for a specific next content task.
medium: clear actionable demand with meaningful engagement or a concrete scenario/counterexample.
low: isolated, generic, low-engagement, vague, joking, or weakly related signal.

Output Contribution

Contribute comment demand signals, demand strength, and possible next content questions.

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Skill: comment_signal_diagnosis

Mission

Read comments as demand signals, not as proof.

Comments should help ReCast decide whether the audience is asking for a next content asset.

Comment Signal Types

explanation_demand: "why is this true?"

comparison_demand: "A or B, which is better?"

tutorial_demand: "how do I do this?"

skepticism: "is this actually true?"

access_or_buying_question: "how do I get/use/buy this?"

counterexample: "my experience differs"

use_case_request: "can you test this scenario?"

joke_or_noise: not actionable unless it reveals a repeated audience frame

Product Decision It Supports

This skill tells later stages whether comments can trigger follow-up content.

Rules

A comment is a signal, not factual evidence.

High likes or replies increase demand strength, not factual truth.

Do not let one funny comment dominate unless it points to a real recurring question.

Do not let one isolated low-engagement comment dominate unless it contains a concrete use case, specific counterexample, or repeated audience frame.

Generic challenges such as "你真的会用吗" are weak skepticism by default. They become medium or high only when the engagement, replies, or concrete reasoning shows real audience demand.

Comments with no substantive demand, such as spam, solicitation, ads, or "代充" offers, are joke_or_noise or irrelevant. They must not be classified as access_or_buying_question.

Comment strength must combine semantic specificity, engagement, and repetition. Semantics alone is not enough to mark a signal medium.

If a comment is low-engagement and does not ask for a concrete test, explanation, tutorial, or counterexample, keep it low or omit it from demand signals.

Preserve the user wording when it is a strong hook.

Strength Calibration

high: many likes/replies, repeated across comments, or asks for a specific next content task.

medium: clear actionable demand with meaningful engagement or a concrete scenario/counterexample.

low: isolated, generic, low-engagement, vague, joking, or weakly related signal.

Output Contribution

Contribute comment demand signals, demand strength, and possible next content questions.