Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/wesleysimplicio/simplicio-loop/simplicio-learnnpx skills add wesleysimplicio/simplicio-loop --skill simplicio-learngit clone --depth 1 https://github.com/wesleysimplicio/simplicio-loopWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00109 | $0.01302 |
| Opus 5 | $0.00055 | $0.00651 |
| Sonnet 5 | $0.00022 | $0.00260 |
| Haiku 4.5 | $0.00011 | $0.00130 |
Grade A, and why
simplicio-learn scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
simplicio-learn — retrospective & continual memory
A run that doesn't record its lessons pays full price every time. This skill turns a finished
run (or session) into a few durable, reusable bullets and writes them where the NEXT run will
read them — closing the simplicio-tasks trajectory/learn/reuse_precedent loop.
Credit: folds cursor continual-learning (transcript-driven, incremental, high-signal-only memory updates with an index to avoid reprocessing) and teaching (a retrospective step that updates persistent state so the next cycle doesn't re-derive what's known).
When to use
- After
simplicio-tasksfinishes its Step 6 self-audit (per-item and per-run). - At session end (bind to a
stophook where available — seehooks/). - "remember this", "retrospective", "what did we learn", "update the project memory".
What to capture (high-signal only)
Three durable categories — everything else is noise and is dropped:
- Corrections — a command that failed then a near-identical one succeeded. Record
{wrong-pattern → right-pattern, error-class, count}. Classify the error (unknown-flag, command-not-found, wrong-syntax, wrong-path, missing-arg, permission-denied). Keep only pairs above ~0.6 command-similarity. EXCLUDE compile/test failures (those are the Step 4 iterate-until-green loop, not a CLI lesson) and human-rejections (a declined action is not an error). - Solved precedents — a problem fingerprint → the solution shape that worked, so a future matching item is REUSED not regenerated. Store fingerprint + PR/commit link + the key edit.
- Bug patterns — structured root-cause pattern store (
.simplicio/orchestrator/patterns.jsonl). Each entry:fingerprint: sha256 of root_cause + fileroot_cause: the mechanism-level root causesymptom_pattern: observable behaviorfix_summary: what fixed itsibling_files: related files changedhit_count: incremented when the same fingerprint is seen againlast_seen: ISO timestamp
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 99 lines · 109 tokens per session scan A b79a0d8fb5a7
simplicio-learn is a skill published in the GitHub repository wesleysimplicio/simplicio-loop (2 stars, last pushed 2d ago), licensed MIT. It adds 109 tokens to every session and 1,302 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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