Make a native static planning Pin and a checked companion knowledge pack.
Finish with: A reviewed static planning Pin for Small entryway planning, controlled A/B drafts, complete native production/capstone plans, an evidence rubric, source-linked retrieval objects and hash-checked companion resources.
Progress stays in this browser. Export to keep a portable record.
BuildBotsBetterA step demonstration outline; use optional narration while you follow it.
This browser checks the evidence format and your checklist. It cannot inspect your computer or certify a live login.
You have recorded evidence for every step. Repeat the core task from a fresh input and export your results. Review the source, account and platform limits before using the workflow on real work.
Produce your native static planning Pin and its same-topic comparison, complete the detailed capstone plan, then review source facts, rights, current community rules and actual media. Run the meaningful failure/repair and source-linked retrieval checks. Export course evidence. A structural pack pass is separate from live publication, audience results or independent quality approval.
Sources checked 2026-10-06. Platform access, account features and upload limits require current account checks. No content was published and no genuine audience metrics or AI citations are claimed. Studio and lint check draft structure; factual accuracy, media quality, OCR/ASR and community fit need human review. The provided fixture is synthetic. Actual content creation and live feedback must not be inferred from a browser walkthrough.
Source-owned text for offline reading and retrieval. Command success still requires actual local evidence.
Download the resource ZIP and extract it into a new private folder. Open studio.html directly in your browser. Compare the two static planning Pin drafts for Small entryway planning. Read AGENT_OPERATING_MANUAL.md and all twenty points in agent-training.json: native CTA/AI, concrete inputs, draft outputs and stop rules. Inspect strategy.json and assign an artifact to each maturity stage. No account or terminal is needed for the studio; do not publish a synthetic fixture.
Expected: The studio shows A/B drafts and a zero-initialized rubric; the content-agent plan has twenty operating points and native CTA/AI boundaries.
Describe visual search, discovery, recommendation, bookmarking, ideas, planning, learning and shopping. Pick future planning rather than momentary entertainment as this Pin purpose.
Expected: Eight functions lead to a planning-first audience decision.
Review two public small-space Pins and their destinations. Record what a user might save today and use later. Do not promise a fixed shelf life or claim one interest is every user’s number-one use case.
Expected: Two dated Pin observations support the future-use persona.
Sketch entryway layout, checklist, comparison chart, decision tree and step sequence. Select the diagram because spatial placement is easier to understand visually.
Expected: Five candidate assets and a justified visual choice exist.
Edit native.json: title, description, alt text, 2:3 image ratio, relevant board and matching destination. Confirm current limits from the linked official source or composer before real upload.
Expected: The card describes a complete static planning Pin.
Make a 2:3 layout sketch with focal object, generous margins, limited overlay text and distinct labels. Preview at 390px and ask a reader to identify the hooks and shelf.
Expected: The phone-size readability observation identifies both objects.
Storyboard silent-understandable 5–10, 10–30, 30–60 second and 1–3 minute alternatives. Use these as editorial pacing options, not platform minimum or maximum limits; label a before/after planning view.
Expected: Four pacing options include visible steps and captions.
Adapt a fast TikTok makeover, a long YouTube tour and a multi-lesson course into a Pin gateway. Each version delivers a saveable layout and matching destination rather than an unrelated repost.
Expected: Three transformation notes preserve planning intent.
Open studio.html. Keep the entryway layout and static format fixed across A/B. Add wall hooks, practical context and a save-for-later purpose while retaining aesthetic appeal.
Expected: A/B drafts refer to the same planned space.
Ask whether a renter would return to this layout in six months. Add dimensions-to-measure and a hardware-permission caveat to the guide, rather than claiming tested installation.
Expected: A future-use checklist explains what remains to be verified.
Draft three tightly focused boards with descriptions and a relevant section for entryways. Show Pin → board → related plan → guide relationships; avoid unrelated trend placement.
Expected: Three board concepts have coherent topic scope.
Record a seed query, guided suggestions if available, planning intent and three long-tail phrases. Describe named objects naturally in title and description.
Expected: A dated search brief and metadata contain no stuffed keyword list.
Compare a clean labeled diagram with a decorative text-heavy mood image. Explain object recognition, OCR and visual similarity as mechanisms, without inventing your asset’s recognition accuracy.
Expected: A human reading test distinguishes observed labels from assumed machine output.
Read a primary source on Pixie or PinSage. Record publication date, inputs, graph/visual use, user purpose, possible content relevance and one limit. Historical architecture is not an exact current ranking contract.
Expected: Six AI evaluation fields distinguish paper evidence from ranking speculation.
Plan definition, how-to, checklist, comparison, diagram, short demo, mistake, tip, FAQ and complete-guide Pin. Keep the small-entryway topic and honest installation boundary across all ten.
Expected: Ten distinct asset briefs share one source object.
Plan an 80/20 editorial mix of enduring small-space layout principles and current decor variations. Add a review date for hardware or destination changes; the ratio is a planning model.
Expected: A dated content calendar explains the optional 80/20 mix.
Review descriptive filename, title, description, alt text, board and direct guide URL. Open the real destination before approving upload; check topic options available in your composer instead of inventing required tags.
Expected: The destination matches the pictured layout and accessibility description.
Sketch a small Buzz guide callout that helps explain one measurement. Compare readability with and without the character; decorative branding must not obscure the actual plan.
Expected: A clear asset has a useful, optional guide character.
Map fourteen stages from source extraction, research and design through metadata, board, destination, score, validation, publication review, analytics and feedback. Adapt the diagram into a YouTube image, LinkedIn document, Reddit gallery and vertical demo.
Expected: A fourteen-stage flow and four format adaptations exist.
Define impressions, Pin clicks, saves, outbound clicks, duration and follows. Specify save rate, CTR and subjective KVS/EMS/VCI with denominators. Test format, ratio, length, headline and palette separately.
Expected: Five controlled tests and metric definitions avoid fabricated results.
Review visual suitability, ratio, phone type, title, description, stuffing, labels, link, board, available relevant topics, AI disclosure, save-worthiness, local cards, promotional risk, score, safeguards and feedback. Build the ten-Pin draft cluster and retain unverified publication status. Review the primary native AI source in AGENT_OPERATING_MANUAL.md. Record documented inputs/outputs, actual account availability (or NOT VERIFIED), a useful native application and a privacy/failure limit. Use this platform’s CTA chain from agent-training.json, rather than importing another platform’s CTA.
Expected: Seventeen checks and ten cluster briefs support a concrete approval decision.
Download the resource ZIP at the top of this Build. Extract it into a new folder you own (for example C:\BBBPractice on Windows, or ~/bbb-practice on macOS/Linux). Open a terminal in the extracted folder. Run the version command for your platform. All subsequent commands assume this folder.
Expected: Python reports version 3.10 or newer and the terminal is in the extracted resource folder.
python --version
Get-Location
Get-ChildItempython3 --version
pwd
lspython3 --version
pwd
lsRead mechanisms.md and claims.json. Attach a direct source and date to established claims; distinguish hypothesis from evidence and future SI from deployed features. Edit knowledge.json and rag.jsonl so each answer stands alone with named entities and a source.
Expected: The ledger separates training, retrieval, indexing, context, citation and action; two source-linked chunks stand alone.
Open studio.html and score each dimension from 0 to 10 with a written reason. Download versions.json and rubric.json; replace the matching extracted files after reviewing them. Leave metrics.json NOT RUN unless you have actual observations. Facebook uses eleven dimensions normalized by dividing by 110 and multiplying by 100.
Expected: A downloadable pair and rubric are saved; the score is self-assessment and unrun metrics are explicit.
Review your changes first. Run the hash command, then lint and score. Inspect report.json. Commands use the current extracted resource folder; PowerShell runs python, macOS zsh and Linux bash run python3. A missing field must be corrected before hashing again.
Expected: HASH PASS and MEDIA PASS appear with exit 0; the readiness score matches the reviewed rubric.
python media_pack.py hash
python media_pack.py lint
python media_pack.py scorepython3 media_pack.py hash
python3 media_pack.py lint
python3 media_pack.py scorepython3 media_pack.py hash
python3 media_pack.py lint
python3 media_pack.py scoreChange versions.json B.topic to a different topic. Run lint and retain MEDIA FAIL. Restore the same topic, review the repair, hash and lint again. Do not weaken the checker or present a structural pass as factual/media verification.
Expected: A mismatched topic produces MEDIA FAIL; a reviewed correction produces MEDIA PASS.
python media_pack.py lint
# After correcting and reviewing the topic:
python media_pack.py hash
python media_pack.py lintpython3 media_pack.py lint
# After correcting and reviewing the topic:
python3 media_pack.py hash
python3 media_pack.py lintpython3 media_pack.py lint
# After correcting and reviewing the topic:
python3 media_pack.py hash
python3 media_pack.py lintRun the supplied question, then an unrelated query. Inspect the answer and source. This standard-library demo uses lexical word overlap, not embeddings, a vector database or an AI citation measurement. Save actual OS command/exit/output and mark other OS branches unverified.
Expected: The relevant query returns source-linked chunks; the unrelated query abstains.
python media_pack.py retrieve --query "What should a small entryway planning Pin make explicit?"
python media_pack.py retrieve --query "quasar waffle weather"python3 media_pack.py retrieve --query "What should a small entryway planning Pin make explicit?"
python3 media_pack.py retrieve --query "quasar waffle weather"python3 media_pack.py retrieve --query "What should a small entryway planning Pin make explicit?"
python3 media_pack.py retrieve --query "quasar waffle weather"Use provenance-notes.md to record author, capture/source dates, rights, AI assistance and unresolved claims. SHA256 detects byte changes but does not sign the file or prove truth. Read the source/command cards, review the native capstone and export course evidence. Actual publication requires your own account, current rules and a human decision.
Expected: The handoff includes native drafts, source/rights review, unsigned integrity manifest, explicit live-status limits and an approval decision.
Fill in onboarding-checklist.md for your agent. Record AGENTS.md, the tool’s user settings and memory folder, the assigned workspace, permissions, guard location, backup schedule, and a final proof task. Keep the checklist in your project.
Expected: The checklist contains a concrete path and owner for rules, memory, permissions, guard, backup, restore and final verification.
Run workspace_guard.py --self-test. Read the source: the target is resolved before deciding. The variable_target case points at the home folder but performs no filesystem operation. Compare this with a hook that sees only command text.
Expected: GUARD PASS reports inside allowed and profile, outside, variable-derived profile and workspace root denied; no deletion was executed.
python workspace_guard.py --self-testpython3 workspace_guard.py --self-testpython3 workspace_guard.py --self-testFor CLI tools, open the hook/permissions screen and confirm the configured guard is active. Use your tool’s documented pre-command hook protocol; the BBB working reference is linked in Sources. Run a harmless directory listing, then a guard dry-run targeting the profile. Do not execute a destructive profile probe. Grok Bot has no proven local shell guard here: use project-only tasks and reviewed actions, with backups.
Expected: A harmless command runs, the guard dry-run returns DENY, and the checklist records the actual hook protocol and active state or the Grok Bot limitation.
Connect a second backup drive. Windows: configure System Protection as additional recovery and use a scheduled copy/File History that explicitly includes hidden agent folders. macOS: configure Time Machine and verify dot folders are included. Linux: use a home backup such as restic/Deja Dup; Timeshift omits /home by default. Download the copy-only profile backup script for your platform, inspect it, and adapt the folder list to your tool. Record the last successful scheduled run; protect backup access because it may contain credentials.
Expected: A backup on another drive includes the tool’s user settings and memory folder and this project, and a successful schedule/time is recorded.
.\profile-backup.ps1 -Destination D:\Backups\llm-profilesbash profile-backup.sh /Volumes/YourBackup/llm-profilesbash profile-backup.sh /media/YourBackup/llm-profilesRun restore_drill.py with a separate backup directory. The script creates a new proof file, copies it, restores a second copy, and compares SHA256 hashes. Then restore one non-secret file from your actual agent memory backup into a separate scratch directory and open it; do not overwrite the live profile.
Expected: RESTORE PASS contains matching hashes; the actual memory file is readable after restoration into scratch.
python restore_drill.py --backup-root D:\Backups\bbb-practice --work-root practicepython3 restore_drill.py --backup-root /Volumes/YourBackup/bbb-practice --work-root practicepython3 restore_drill.py --backup-root /media/YourBackup/bbb-practice --work-root practice