Ambiguity and learning
Skill AnamKwon/agent-skill-router/plugins/skill-router/skills/ambiguity-and-learning
Cross-agent skill router that organizes large local skill libraries into category routers and loads leaf skills on demand.
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Use first for ambiguous failures, messy project context, surprising results, repeated failures, postmortems, or contested product and architecture framing.
SKILL.md
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Ambiguity and Learning
Use first for ambiguous failures, messy project context, surprising results, repeated failures, postmortems, or contested product and architecture framing. This is a router skill: use it to select the smallest relevant leaf skill, then read that leaf skill before doing the work.
Route First
Do not pick a design leaf until the uncertainty shape is clear: cues, surprise, repeated governing assumption, or stakeholder conflict.
- Restate the user's task as one concrete force or uncertainty.
- Choose the first route that directly names that force.
- Read the selected linked leaf
SKILL.mdbefore implementing, reviewing, or advising. - Load a second leaf only when the task has two independent forces that both affect the outcome.
- If no route fits, continue without a leaf skill and say the category did not match.
Routes
| Leaf Skill | Use When |
|---|---|
sensemaking | Use when logs, errors, reports, or legacy context need a plausible working story before action. |
reflective-practice | Use when a surprising result during work should reframe the next move. |
double-loop-learning | Use when repeated failures point to a bad assumption, default, policy, metric, or governing variable. |
wicked-problems | Use when problem definition, stakeholder criteria, or product/architecture tradeoffs are contested. |
situated-action | Use when new local evidence invalidates the current plan and the next step must adapt. |
Avoid
- If the problem is already well-bounded and technical, route to the matching implementation category.
- If the next action would require a product, legal, security, or organizational decision, stop and gather context.
Prompting Pattern
Before loading a leaf, answer briefly:
- Category force: What makes this task belong here?
- Chosen route: Which leaf skill most directly matches the force?
- Why not others: Which nearby route was rejected and why?
Then load the chosen leaf skill and follow its workflow. Do not blend every nearby theory into the task; route narrowly and let evidence pull in more context only when needed.