grasp

Solid

Verify understanding after AI work through intent-scented entry points. Type: (ResultUngrasped, User, VERIFY, Result) → VerifiedUnderstanding. Alias: Katalepsis(κατάληψις).

AI & Automation 161 stars 15 forks Updated today MIT

Install

View on GitHub

Quality Score: 84/100

Stars 20%
74
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Katalepsis Protocol Achieve certain comprehension of AI work through structured verification, enabling the user to grasp ungrasped results. Type: `(ResultUngrasped, User, VERIFY, Result) → VerifiedUnderstanding`. ## Definition **Katalepsis** (κατάληψις): A dialogical act of achieving firm comprehension—from Stoic philosophy meaning "a grasping firmly"—resolving ungrasped AI-generated results into verified user understanding through intent-scented entry points and progressive verification. ``` ── FLOW ── (R, U) → I → E → Fᵣ → Sₑ → B → Tᵣ → detect(E, B) → GT → P → Δ → Q → A → P' → Tᵤ → Q(coverage) → (loop until katalepsis) ── MORPHISM ── Result → orient(result, user_signal) -- infer likely comprehension intents from AI work and user's wording → derive_entries(intent) -- transform inferred intent into high-scent entry points → assess_route(intents, entries, R, U, context) -- annotate entry-point adequacy before user selection → select(intent_entry_point, route_map) -- user chooses the closest intent-scented entry point → materialize(artifact_basis) -- derive concrete artifact anchors for the chosen intent → register(tasks) -- track selected entry points as tasks → verify(comprehension) -- Socratic probing per gap type → confirm(coverage) -- aspect coverage check per entry point → VerifiedUnderstanding requires: result_exists(R) -- AI work output must exist in context def...

Details

Author
jongwony
Repository
jongwony/epistemic-protocols
Created
8 months ago
Last Updated
today
Language
JavaScript
License
MIT

Bundled in these plugins

Similar Skills

Semantically similar based on skill content — not just same category

Web & Frontend Solid

inquire

Infer context insufficiency before execution. Surfaces uncertainties through information-gain prioritized inquiry when AI infers areas of context insufficiency, producing informed execution. Type: (ContextInsufficient, AI, INQUIRE, Prospect) → InformedExecution. Alias: Aitesis(αἴτησις).

161 Updated today
jongwony
AI & Automation Listed

comprehend

Agent→human teach-to-mastery loop. Turns the agent into a wise, effective teacher whose single objective is that YOU deeply understand a body of work — the problem and why it existed, the solution and why it was resolved that way (design decisions, edge cases), and the broader context (why it matters, what it impacts). Stage-gated (confirm mastery before advancing), active-recall driven (you restate first; the agent fills gaps; quizzes via AskUserQuestion), and goal-bounded (the session does not end until your understanding is verified). Default subject = the current session/diff; pass a PR number, file, or subsystem to teach that instead. The pedagogical INVERSE of grill-me: grill-me stress-tests YOUR forward plan; comprehend transfers mastery of EXISTING work to you. Distinct from handoff (agent→agent narrative) and Bridge/Bookkeeping (agent→KG). Use when: (1) you want to deeply understand what was just built, (2) onboarding yourself or a teammate onto a PR / file / subsystem, (3) post-mortem learning after

3 Updated today
broomva
AI & Automation Solid

induce

Calibrate and crystallize in-process abstraction through dialectical triangulation. Proposes calibrated candidate abstractions with personalized grounding examples and shapes them via user widen/narrow/fuse/reorient moves when an instance set has converged toward an unnamed essence, producing crystallized abstraction. Type: (AbstractionInProcess, AI, INDUCE, A) → CrystallizedAbstraction. Alias: Periagoge(περιαγωγή).

161 Updated today
jongwony