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 skills add aget-framework/template-advisor-aget --skill aget-record-lessongit clone --depth 1 https://github.com/aget-framework/template-advisor-agetWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aget-framework/template-advisor-aget/aget-record-lesson)<a href="https://agentmods.dev/skills/aget-framework/template-advisor-aget/aget-record-lesson"><img src="https://agentmods.dev/badge/skills/aget-framework/template-advisor-aget/aget-record-lesson/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aget-framework/template-advisor-aget/aget-record-lesson"><img src="https://agentmods.dev/badge/skills/aget-framework/template-advisor-aget/aget-record-lesson.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00039 | $0.01305 |
| Opus 5 | $0.00019 | $0.00652 |
| Sonnet 5 | $0.00008 | $0.00261 |
| Haiku 4.5 | $0.00004 | $0.00130 |
Grade A, and why
aget-record-lesson 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 9d 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.
This is a copy
100% identical to aget-record-lesson — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/aget-record-lesson
Record lessons learned as structured L-docs in the git repo. Each lesson is classified to determine storage location and ID scheme.
Purpose
Capture learnings in a persistent, searchable format that survives context windows and session boundaries. Enables knowledge accumulation across sessions.
Input
$ARGUMENTS - Optional lesson description or trigger context
Execution
Step 1: Gather Context
Identify what triggered the lesson:
- Session observation
- User feedback
- Error encountered
- Pattern discovered
- Process improvement
Step 2: Classify the Lesson
Ask the user:
Classification Required
Would this lesson help another AGET (different principal, different domain)?
- Framework → Reusable across AGETs →
.aget/evolution/L###_*.md- Domain → Helps this principal →
knowledge/patterns/*.md
Decision Tree:
Would this help another AGET?
├── YES → Framework → .aget/evolution/L###_{name}.md (gets L-number)
└── NO → Would this help the principal without an AGET?
├── YES → Domain → knowledge/patterns/{category}/{name}.md
└── UNCLEAR → Ask user to clarify
Step 3: Get Next ID (Framework only)
# Read next_id from index.json
jq '.next_id' .aget/evolution/index.json
Step 4: Create Lesson Document
Framework Template (.aget/evolution/L{ID}_{name}.md):
# L{ID}: {Title}
**Date**: {YYYY-MM-DD}
**Type**: Lesson Learned
**Category**: {category}
**Status**: complete
---
## Summary
{One paragraph summary of the lesson}
---
## Context
{What triggered this lesson? What were you doing?}
---
## Key Finding
{The core insight or learning}
---
## Implications
{What should change as a result?}
---
## Traceability
| Link | Reference |
|------|-----------|
| Session | {session file if applicable} |
| Project | {project plan if applicable} |
| Trigger | {what prompted this lesson} |
---
*L{ID}: {Title}*
*Category: {category}*
Domain Template (knowledge/patterns/{category}/{name}.md):
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.
- 9d ago First seen · 192 lines · 39 tokens per session scan A dee908c7f924
aget-record-lesson is a skill published in the GitHub repository aget-framework/template-advisor-aget (2 stars, last pushed 10d ago), licensed Apache-2.0. It adds 39 tokens to every session and 1,305 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to aget-record-lesson, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
init
Turn on Rekal memory in the current repository by running rekal init. Use when the user asks to initialize or set up Rekal here, or when a rekal command reported the repository is not initialized. Once per repository. Do not offer this merely because a repo lacks a .rekal/ store — most repos do not want one.
metagit-context-pack
Token-efficient workspace onboarding via tiered context packs — map, repo cards, session digest, objectives, approvals, repomix profiles. Use at session start or when scoping work in a metagit-managed workspace.
unforgit-memory
Use Unforgit MCP tools as durable repository memory for decisions, conventions, gotchas, and playbooks.
loredex-sync
Commit local dex changes, pull teammates' notes, push yours — the team-sharing loop for a git-backed dex. Use when the user says "sync the dex", "push my notes", "pull the latest dex", or after finishing work another team should see.
project-memory
GitHub-native persistence for project learnings, decisions, and patterns using issue labels and structured comments. Used when recording what worked, what failed, or architectural decisions that should persist across sessions.
repo-hygiene
Use when the scheduled repo-hygiene workflow runs from GitHub Actions (or an operator dry-run) to scan the repository for small, certain docs/test/code hygiene issues and fix them as one batched branch.