LearnCAUTION
A framework for building agentic apps
Overview
A framework for building agentic apps
d31edd75948aOBSERVED · 2026-10-14What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: learn
description: >
Extract key learnings from the current chat thread and save them to docs/learnings.md.
Use this skill when the user types "/learn" or asks to save learnings from the conversation.
---
# Learn Skill
## When to Use
- User types `/learn` in chat
- User asks to "save this as a learning", "remember this", or "add this to learnings"
- User corrects you and you want to persist that correction for future sessions
## How It Works
1. Review the full conversation thread
2. Identify corrections, preferences, data mappings, workflow insights, and gotchas
3. Save each learning via `POST /api/learn`
4. Confirm what was saved
## API Endpoint
### `POST /api/learn`
Appends a structured entry to `docs/learnings.md`.
**Structured entry** (preferred for individual learnings):
```json
{
"category": "User Preferences",
"insight": "Always filter out internal team emails when showing customer-specific activity",
"source": "User correction during customer dashboard session"
}
```
**Raw markdown** (for complex multi-line entries):
```json
{
"rawMarkdown": "### Customer Data\n\n**Example Corp** org ID: `example-org-id`. Primary contact: [email protected]."
}
```
### `GET /api/learn`
Returns the current contents of `docs/learnings.md` as `{ content: string }`.
## Valid Categories
Use one of the existing section headers from `docs/learnings.md`:
- `Agent Behavior Rules`
- `Customer Data`
- `User Preferences`
- `UI Patterns`
- `Dashboard Data Fetching Pattern`
- `Reusable Scripts`
- `Cross-Referencing Customers Across Services`
Use `Other` if none fit — the learning will be appended at the end of the file.
## What to Extract
When reviewing a thread, focus on:
| Signal | Example |
| ------------------------ | ----------------------------------------------------------- |
| **User corrections** | "No, that metric should use `signup` not `sign_up`" |
| **Data source mappings** | "Example Corp org IDs are X, Y, Z" |
| **Query patterns** | "Always join on `dim_hs_contacts` for customer lookups" |
| **Preferences** | "I prefer stacked bar charts for per-user breakdowns" |
| **Gotchas** | "The `data` column is JSON — use `JSON_VALUE()` to extract" |
| **Workflow insights** | "Check Grafana before looking at code for incidents" |
**Skip** obvious or trivial observations. Each learning should be actionable — what to do, what not to do, and why.
## Example Flow
User types `/learn`. Agent responds:
1. Scan the thread for corrections and insights
2. For each learning found, call `POST /api/learn`:
```
POST /api/learn
{ "category": "Customer Data", "insight": "Example Corp org ID is `example-org-id`", "source": "Thread with Steve" }
```
3. Summarize what was saved:
> Saved 3 learnings to `docs/learnings.md`:
>
> - **Customer Data**: Example Corp org ID is `example-org-id`
> - **User Preferences**: Use dark theme for all exported charts
> - **Agent Behavior Rules**: Always check Sentry before investigating code for error spikes
## Gotchas
- Always read `docs/learnings.md` first to avoid duplicating existing entries
- Keep insights concise — one actionable point per entry
- Use the structured format (category + insight + source) for most entries; raw markdown only for complex multi-line content
- The `source` field is optional but helpful for traceabilityTrust audit
CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (5)
.agents/skills/an
.agents/skills/content-product-development
.agents/skills/design-exploration
.agents/skills/turn-into-app
.agents/skills/visual-edit
Gates applied: no_behavioural_pass.
d31edd75948afull audit observations/trust-audit/skill/builderio__learn.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-14 | d31edd75948a | CAUTION | B | 89 | first audit |
Questions
What does the Learn skill do?
A framework for building agentic apps
Is Learn safe to install?
With care. The audit graded it B (89/100) and found 5 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can Learn access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (d31edd75948a), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.
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[](https://modelsatlas.com/skills/builderio/learn/)
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