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 commands/zingspark/create-harness-vibe-coding/wf-learngit clone --depth 1 https://github.com/zingspark/create-harness-vibe-codingWrote 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/commands/zingspark/create-harness-vibe-coding/wf-learn)<a href="https://agentmods.dev/commands/zingspark/create-harness-vibe-coding/wf-learn"><img src="https://agentmods.dev/badge/commands/zingspark/create-harness-vibe-coding/wf-learn.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.00202 |
| Opus 5 | $0.00008 | $0.00101 |
| Sonnet 5 | $0.00003 | $0.00040 |
| Haiku 4.5 | $0.00002 | $0.00020 |
Grade A, and why
wf-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 5d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 5d ago First seen · 17 lines · 15 tokens per session scan A 02606f2a91e0
wf-learn is a command published in the GitHub repository zingspark/create-harness-vibe-coding (5 stars, last pushed 1mo ago), with no licence file. It adds 15 tokens to every session and 202 once invoked, about $0.0001 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.
Other commands, from other repositories
learn-pending
List all staged learning changes awaiting approval.
learn
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train-executor
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training-coach-trainer
Train-the-trainer (TtT) protocol for internal subject-matter-experts who will deliver a training program. Condensed adult-learning principles, facilitation skills, common SME-as-trainer failure modes, cohort facilitation practice schedule, and a TtT-readiness rubric. Refuses SME deployment without TtT.
training-curriculum
Outcome-back curriculum design for a single program or module. Starts from the L3 job behavior change and L4 business outcome; works backward through capability requirements, sequencing, spaced retrieval, cognitive-load chunking, encoding-context simulation, and per-module evaluation rubric. Refuses content-first…
training-measure-transfer
Kirkpatrick L3 (behavior) + L4 (results) measurement plan for a training program. Behavior observation protocol with sampling cadence, business-metric tracking, post-program reinforcement plan, redesign feedback loop. Refuses L1-only smile-sheet evaluation; refuses programs without baseline.