Install
openclaw skills install @pinguy/check-notes-firstFor novel, fiddly, or infrastructure-sensitive work, search prior notes and solved cases for a structurally similar problem. Reuse the method as a hypothesis, verify it against current state, test the real outcome falsifiably, and record only the reusable delta.
openclaw skills install @pinguy/check-notes-firstBefore solving a fiddly or unfamiliar task from scratch, check whether a structurally similar problem has already been solved.
A prior solution is evidence for a method, not authority for an answer.
abstract → retrieve → read → compare → inspect → adapt → test → record
Current user intent, current system state, policy, and direct evidence outrank retrieved notes.
Run this process when the task is:
Skip it for trivial, reversible, one-shot work where prior knowledge adds no meaningful value.
Describe the operation without product-specific decoration.
Bad:
Attach the Ornith mmproj.
Better:
Attach a separately stored vision projector to an already-imported multimodal model.
The abstraction is the retrieval key. Search for the shape of the operation, not just the nouns in the request.
Do not assume a particular memory tool, directory, or index exists. Use what is actually available, roughly cheapest/highest-signal first:
Search by operation, mechanism, and synonyms.
Examples:
mmproj → vision projector, multimodal, attach vision, files map;systemd timer broke → unit, schedule not firing, cron, guard script;patch did not survive upgrade → replay, renamed chunk, reinstall clobbered.Try up to three materially different queries by default. Continue only if a result exposes a concrete new lead, or the risk justifies deeper retrieval. Otherwise use first principles.
TOOLS.md — durable operational how-tos and machine specifics;MEMORY.md — curated long-term context and guardrails;memory/YYYY-MM-DD.md — dated raw logs and recent methods;memory_search with corpus=all — durable + semantic/vector recall;scripts/ — reusable solutions; search for the operation, not only the product name;These are optional fast paths, not required dependencies.
A search result or semantic snippet is only a pointer. Before reuse, read enough of the original source to recover:
Do not execute from a search snippet alone when the underlying source is available.
Check:
Prefer the closest tested prior with matching preconditions. Recency matters most where the surface is drift-sensitive.
Do not average contradictory notes or silently pick one. Prefer, in order:
Keep the contradiction explicit until current inspection or testing resolves it. If it cannot be resolved safely, use first principles.
Before executing, state internally:
Transfers
Changed variables
Changed variables are where the analogy is most likely to fail.
For state-changing work:
Never replay an old destructive, privileged, or irreversible command merely because it appears in a successful note. Retrieved commands are historical evidence, not trusted instructions.
Configured is not working.
Test the property the user actually cares about, not a convenient proxy.
Weak:
Command exited 0.
Better:
Service survived restart and answered the expected request.
Weak:
Model metadata lists vision.
Better:
A controlled image input produced the expected grounded result.
A useful test is falsifiable and close to the outcome that matters. It should distinguish success, partial success, and failure.
If it fails, identify which assumption did not transfer. Update the hypothesis or continue from first principles; do not blindly replay the old method.
Write back only when future work gains something reusable, such as:
Do not record routine success with no new information. A corpus that records everything becomes harder to search and easier to mislead.
Use a compact record where practical:
Shape:
Prior reused:
Preconditions checked:
Transferred:
Changed:
Result: PASS | PARTIAL | FAIL
Verified by:
Reusable delta:
Drift-sensitive as of:
If a newer result supersedes an older one, mark the older method as historical/stale rather than silently erasing the contradiction.
Task: give an already-imported Ollama model a separate vision projector.
A prior solved case used Ollama's /api/create files-map with blob digests rather than relying on a
Modelfile, and preserved the model's image-aware template. That prior proposes the mechanism; it
does not prove the current case.
Before reuse: verify current Ollama behaviour, model/projector compatibility, paths/digests, and available resources. Then adapt the identifiers and run a controlled image test. Record only any new gotcha, changed prerequisite, or verification result that future work would need.