بنقرة واحدة
consolidate-memory
Reflective pass over your memory files — merge duplicates, fix stale facts, prune the index.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Reflective pass over your memory files — merge duplicates, fix stale facts, prune the index.
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
Set up Cloudflare Turnstile end-to-end in a project: scan the codebase, create the widget via the Cloudflare API, deploy the managed siteverify Worker, write the frontend snippets, validate, and persist the skill. Load this when a user asks to add Turnstile, set up CAPTCHA, protect a form from bots, or fix a Turnstile integration. Mirrors developers.cloudflare.com/turnstile/spin.
Four-phase protocol for clearing accumulated drift between memory claims, CLAUDE.md citations, and on-disk reality. Detects stale citations, missing files, and orphan plans; classifies findings; emits proposed diffs; codifies prevention. Companion to closeout (closeout discovers orphans; this skill polishes them). Discovery ≠ remediation — Phase 3 emits proposed diffs only; constitutional doc edits require explicit conductor authorization.
Ingest a corpus of session logs (JSONL transcripts, chat exports) and extract a persona profile — vocabulary frequency, unique idioms and coinages, structural analogies — then synthesize an ideal_yearning and archetypal_pattern and append the result to a {persona_id}.lexicon.yaml. Triggers on "extract persona", "build a lexicon", "map the domain language", or any request to process conversation logs into a voice/vocabulary model.
Apply narratological scoring to a text, transcript, or recording transcript — rating contiguous spans for pathos, logos, ethos, kairos, and density — then extract the single highest-scoring contiguous block as the work's Natural Center, with a scoring table and justification. Triggers on "find the natural center", "extract the most dramatic moment", "what's the strongest passage", or pulling the peak block from a long artifact for a short, excerpt, or trailer.
Transform any data, document, deck, README, manifest, config, or report by (1) extracting every piece of dynamic information — names, links, statistics, costs, identifiers, dates, thresholds — into configurable variables instead of hard-coding, and (2) enforcing that every factual assertion carries at least two independent citations. Triggers on "remove branding," "make this reusable," "transmute this," "parametrize," "no hard-coded values," "configurable," "needs citations," "verify these claims," or any request to convert a one-off artifact into a parameterized template.
Scan rough markdown, session exports, or pasted prose and isolate each core intent into a structured prompt atom — classified as law, value, directive, constraint, question, or branch-vector — then rewrite it into machine-readable YAML frontmatter per the RAW → CLEANED/FORMALIZED → ELEVATED doctrine. Triggers on "prompt atom extraction pass", "atomize this", "formalize these prompts", or converting loose operator text into registry-grade atoms.
| name | consolidate-memory |
| description | Reflective pass over your memory files — merge duplicates, fix stale facts, prune the index. |
| license | MIT |
You're doing a reflective pass over what you've learned about this user and their work. The goal: a future session should be able to orient quickly — who they work with, what they're focused on, how they like things done — without re-asking.
Your system prompt's auto-memory section defines the directory, file format, and memory types. Follow it.
MEMORY.md)Separate the durable from the dated. Preferences, working style, key relationships, and recurring workflows are durable — keep and sharpen them. Specific projects, deadlines, and one-off tasks are dated — if the date has passed or the work is done, retire the file or fold the lasting takeaway (e.g. "user prefers X format for launch docs") into a durable one.
Merge overlaps. If two files describe the same person, project, or preference, combine into one and keep the richer file's path.
Fix time references. Convert "next week", "this quarter", "by Friday" to absolute dates so they stay readable later.
Drop what's easy to re-find. If a memory just restates something you could pull from the user's calendar, docs, or connected tools on demand, cut it. Keep what's hard to re-derive: stated preferences, context behind a decision, who to go to for what.
Update MEMORY.md so it stays under 200 lines and ~25KB. Each entry is one line, under ~150 chars, in this format:
- [Title](file.md) — one-line hook
Finish with a short summary: how many files you touched and what changed.