القائمة
In-Context Learning — select and inject worked examples (demos) before executing recurring task types. Load when a task matches a known pattern family.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Context engineering — memory navigation, textual graph traversal, progressive disclosure, recovery. Load when assembling context for a task or when lost.
Implementation-side security discipline — headers, dependencies, secrets, authz. Load for hardening work (sec-ops domain).
Commit conventions, branching, anchors in messages, and the git safety rules. Load for any git operation beyond status/diff.
Anti-generic-AI design discipline — bans, tells, and the slop test. Load for ANY new UI surface or visual redesign. Inspired by Impeccable (Apache 2.0).
Motion & animation discipline — purpose, performance, reduced-motion. Load when work involves animation, transitions or scroll effects.
Microcopy discipline — buttons, errors, empty/loading/success states, alt text. Voice and tone come from the project's memory, not from this skill.
| name | icl |
| description | In-Context Learning — select and inject worked examples (demos) before executing recurring task types. Load when a task matches a known pattern family. |
Injecting 1–2 matched demos before a task measurably beats zero-shot on recurring patterns. The pool lives in .berserqir/skills-resources/icl/demos/ (hub, on-demand regime).
| Resolution | Content | Use for |
|---|---|---|
| task-level | full trajectory of a completed similar task (goal → steps → outcome) | complex multi-step tasks |
| step-level | snippet of one recurring step (e.g., "update memory-medium after task") | protocol steps agents get wrong |
core/protocols/context-budget.md.---
tags: [area, pattern-family]
outcome: success | anti-example
source: manual | promoted-instinct | eval-failure
---
# Goal
# Trajectory (condensed ReAct: thought → action → observation)
# Outcome & verification
Eval failures and recurring errors become outcome: anti-example demos — injected alongside a success demo when the task family has a known failure mode ("this looks right but fails because…").
Demos enter the pool by: manual curation · instinct promotion (confidence ≥ threshold + eval pass — see plan F4) · eval failure capture. Every demo carries source.