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docs(guideline): add PyPI install option and skill-aware reflection config rows

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Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Cuzyoung
2026-06-10 13:27:12 +00:00
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@@ -380,6 +380,15 @@ skillopt/ <span class="tok-c"># the package</span>
<section id="install">
<h2>2.2 Install the Package <a class="anchor" href="#install">#</a></h2>
<p><strong>Option A — from PyPI:</strong></p>
<pre><code><span class="tok-k">pip</span> install skillopt
<span class="tok-c"># Optional extras:</span>
<span class="tok-k">pip</span> install skillopt[alfworld] <span class="tok-c"># ALFWorld benchmark</span>
<span class="tok-k">pip</span> install skillopt[webui] <span class="tok-c"># Gradio monitoring dashboard</span>
<span class="tok-k">pip</span> install skillopt[claude] <span class="tok-c"># Claude model backend</span>
</code></pre>
<p><strong>Option B — from source (for development):</strong></p>
<pre><code><span class="tok-k">git</span> clone https://github.com/microsoft/SkillOpt.git
<span class="tok-k">cd</span> SkillOpt
<span class="tok-k">pip</span> install -e .
@@ -708,6 +717,9 @@ skillopt/ <span class="tok-c"># the package</span>
<tr><td><code>slow_update_gate_with_selection</code></td><td>bool</td><td class="def">false</td><td>—</td><td><code>false</code> = force-inject guidance; <code>true</code> = gate it on the selection split (see §5.4).</td></tr>
<tr><td><code>longitudinal_pair_policy</code></td><td>str</td><td class="def">mixed</td><td>—</td><td><code>mixed</code> / <code>changed</code> / <code>unchanged</code> — which comparison pairs to keep.</td></tr>
<tr><td><code>use_meta_skill</code></td><td>bool</td><td class="def">true</td><td>Meta-learning</td><td>Enable cross-epoch optimizer memory.</td></tr>
<tr><td><code>use_skill_aware_reflection</code></td><td>bool</td><td class="def">false</td><td>—</td><td>EmbodiSkill-style failure routing: <code>SKILL_DEFECT</code> (rule wrong/missing &rarr; gated body edit) vs <code>EXECUTION_LAPSE</code> (valid rule not followed &rarr; reminder appended to a protected appendix region that step-level edits never modify). Off = baseline-identical; resolved process-wide, works on every benchmark. Not supported with <code>rewrite_from_suggestions</code> / full-rewrite modes.</td></tr>
<tr><td><code>skill_aware_appendix_source</code></td><td>str</td><td class="def">both</td><td>—</td><td><code>both</code> (success analyst may also re-emphasize rules) / <code>failure_only</code> (paper-faithful S_app: failure side only).</td></tr>
<tr><td><code>skill_aware_consolidate_threshold</code></td><td>int</td><td class="def">0</td><td>—</td><td><code>&gt;0</code>: LLM-compact the appendix once it exceeds N notes (experimental); <code>0</code> = off.</td></tr>
</tbody>
</table></div>
</section>