计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
s4h-sensory-signal-detection【效率与协作】Separates meaningful signal from background noise — finding what actually matters among everything present. Triggers: 'what actually matters here', 'separate signal from noise', 'too much information', 'find the signal', 'what should I focus on', 'what's relevant'.
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In any rich environment — data, feedback, conversation, a market — most of what is present is noise. Signal is what varies with the thing you're trying to understand; noise varies independently. The challenge is not finding more information, it's knowing which information is doing real work.
Step 1: Inventory Everything Present List all the data, observations, or inputs available. Don't filter yet — complete the inventory first.
Framing check: Confirm the specific subject before continuing. State what you've identified — the actual environment or dataset being analyzed and what outcome or phenomenon the user is trying to understand — in one sentence, then use AskUserQuestion:
Step 2: Variance Test For each item: does it vary with the outcome or phenomenon you're trying to understand? Signal co-varies with what you care about. Noise varies on its own schedule.
Step 3: Persistence Test Is this item consistently present across time and contexts, or did it appear once? Persistent patterns are more likely to be signal. One-off observations may be noise, anomaly, or coincidence.
Step 4: Specificity Test Is this item unique to this situation, or is it always present? Always-present background conditions are usually noise. What is specific to the case is more likely signal.
Step 5: Counterfactual Test If this item changed or disappeared, would the outcome change? If yes: probable signal. If the outcome would be the same regardless: probable noise.
Step 6: Classify and Summarise Assign a classification to each item and present the full classified inventory to the user.
Before narrowing: Show the complete classified set to the user first. Use AskUserQuestion:
Then identify the top signals to act on.
Before proceeding, use the AskUserQuestion tool. State your interpretation of the situation in 1–2 sentences — what is being analyzed and what the core question is — then ask:
Proceed based on their selection. If the user reframes, incorporate the correction before running any analysis.
| Element | Varies with Outcome? | Persistent? | Specific? | Counterfactual? | Classification |
|---|---|---|---|---|---|
| ... | ... | ... | ... | ... | Signal / Noise / Unclear |
Classifications: Clear Signal / Probable Signal / Unclear / Probable Noise / Clear Noise
When in doubt, classify as "unclear" rather than forcing a label — the act of flagging uncertainty is itself useful. Run this when a situation feels overwhelming or when a team is arguing about what matters.
After delivering this output, use AskUserQuestion to offer the next move:
/s4h-sensory-structured-observation — Observe in depth around the detected signals/s4h-aesthetic-pattern-detection — Find patterns in the signals/s4h-systems-feedback-mapping — Map feedback systems the signals reveal