القائمة
Interruption pattern detection and retrieval from Amp thread history. Use for analyzing tool rejection patterns and improving agent behavior.
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
استنادا إلى تصنيف SOC المهني
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/plurigrid/asi --skill amp-skillيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
عرض SKILL.md
Compressive Vasomotion Hypothesis (CVH) — vasomotion as a fast compression sweep that collapses ambivalent neural resonances (the Bayesian-blur problem) into a definite state. Use when modeling the ~100ms taṇhā 'grab', precision-weighting as compression forcefulness, or the generative collapse step of vasocomputational active inference.
Latched Hyperprior Hypothesis (LHH) — a sustained vascular contraction engages the smooth-muscle latch-bridge, durably freezing a circuit as a committed hyperprior isolated from global updating; unlatches when its prediction resolves. Use when modeling durable commitments, trauma/PTSD as cemented priors, latch spirals, or the cross-substrate latch (mechanical/bioelectric/immune/sheaf).
Synaptic substrate of biological active inference — long-term potentiation/depression (LTP/LTD) writes priors into synaptic weights = the learning landscape (Deep CANALs). A held vascular latch annealed long enough crystallizes into a neuron prior. Use when modeling consolidation, neuron priors, the inference→learning landscape write-path, or commit-to-disk of a held prediction.
| name | amp-skill |
| description | Interruption pattern detection and retrieval from Amp thread history. Use for analyzing tool rejection patterns and improving agent behavior. |
| metadata | {"trit":0,"color":"#26D826"} |
GF(3) Trit: 0 (ERGODIC - coordination layer) Foundation: DuckDB ACSet from Amp file-changes
Amp-Skill distills usage patterns from Amp thread history, specifically focusing on interruption patterns where tool suggestions were rejected in favor of:
| Metric | Value |
|---|---|
| Total Threads | 616 |
| Total Tool Calls | 2,535 |
| Threads with Interruptions | 282 (45.8%) |
| Reverted Tool Calls | 84 (3.3%) |
| Two-Lock Cascades | 47 |
| Complete Discontinuations | 22 |
| Pattern Type | Count | Percentage |
|---|---|---|
| abandoned | 269 | 62.4% |
| reverted | 84 | 19.5% |
| two_lock | 47 | 10.9% |
| discontinuation | 22 | 5.1% |
| high_rejection | 9 | 2.1% |
| Role | Threads | Tool Calls | Reverted |
|---|---|---|---|
| MINUS | 218 | 769 | 27 |
| ERGODIC | 209 | 976 | 26 |
| PLUS | 189 | 790 | 31 |
.org - 28 reverts (Emacs org-mode files).py - 20 reverts (Python scripts).sh - 18 reverts (Shell scripts).md - 15 reverts (Markdown documentation)-- Query interruption patterns
SELECT * FROM amp_interruptions ORDER BY ts DESC;
-- Find high-rejection threads
SELECT thread_id, tool_call_count, reverted_count,
ROUND(100.0 * reverted_count / tool_call_count, 1) as revert_pct
FROM amp_threads
WHERE reverted_count > 0
ORDER BY revert_pct DESC;
-- Detect two-lock cascades
SELECT thread_id, COUNT(*) as consecutive_reverts
FROM amp_interruptions
WHERE pattern_type = 'two_lock'
GROUP BY thread_id
ORDER BY consecutive_reverts DESC;
capability-signer-prototype.sh.org files most frequently rejected (28)# Load/refresh Amp threads
bb scripts/amp_thread_loader.bb
# Query via DuckDB
duckdb trit_stream.duckdb "SELECT * FROM amp_interruptions"
When Amp-Skill detects a high-rejection pattern:
~/.amp/file-changes/T-* (2,535 files)