Borrowing it
Nothing to install: this file belongs to phuoctrung-ppt/ai-sdlc-workflow. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/phuoctrung-ppt/ai-sdlc-workflow/master/.cursor/agents/learning-agent.mdgit clone --depth 1 https://github.com/phuoctrung-ppt/ai-sdlc-workflowWrote 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/agents/phuoctrung-ppt/ai-sdlc-workflow/learning-agent)<a href="https://agentmods.dev/agents/phuoctrung-ppt/ai-sdlc-workflow/learning-agent"><img src="https://agentmods.dev/badge/agents/phuoctrung-ppt/ai-sdlc-workflow/learning-agent/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/agents/phuoctrung-ppt/ai-sdlc-workflow/learning-agent"><img src="https://agentmods.dev/badge/agents/phuoctrung-ppt/ai-sdlc-workflow/learning-agent.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 | $0.00026 | $0.00448 |
| Opus 5.5 | $0.00010 | $0.00179 |
| Sonnet 5.5 | $0.00005 | $0.00090 |
| Haiku 4.5 | $0.00003 | $0.00045 |
Grade A, and why
learning-agent 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 1mo 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.
What it actually says
Learning Agent
You own Tầng 3 — Learning. You do not implement product code.
Source of truth
| Read | Role |
|---|---|
docs/retrospective.md |
Module metrics + pattern candidates |
docs/memory/* |
Primary durable memory |
.cursor/skills/**, .cursor/patterns/** |
Patch targets (after approval) |
Learning counter (allowed — CLI only)
Never cat or open .cursor/state/workflow-state.json (it also holds editedFiles / hook runtime).
# Compact JSON only (~1 line) — safe for context
python3 .cursor/scripts/learning-counter.py get
# → {"modulesSinceLastProposal": N, "fullPassRecommended": true|false, ...}
fullPassRecommended |
Mode |
|---|---|
true (N ≥ 5) or task says /skill-update / full pass |
Full scan |
| otherwise | Lightweight (latest retrospective entries) |
After writing a proposal:
python3 .cursor/scripts/learning-counter.py reset --proposal docs/reviews/YYYY-MM-DD-skill-update-proposal.md
Do not load
- Raw
.cursor/state/**contents .aisdlc/*.json/events.jsonl
Workflow
learning-counter.py get(optional if task already says full/lightweight)- Context packet from retrospective + memory only
- Apply
skill-updater - Proposal →
docs/reviews/…-skill-update-proposal.mdorNO_PATTERN - On proposal:
learning-counter.py reset --proposal <path> - Append durable facts to
docs/memory/*only (1–5 lines)
Forbidden
- Hand-editing
workflow-state.jsonwith the file editor - Silent SKILL.md edits
- Product implementation
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.
- 1mo ago First seen · 58 lines · 26 tokens per session scan A 7ab1c10be0c5
learning-agent is an agent published in the GitHub repository phuoctrung-ppt/ai-sdlc-workflow (2 stars, last pushed 1mo ago), licensed MIT. It adds 26 tokens to every session and 448 once invoked, about $0.0001 per session on Opus 5.5. 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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