Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Synaptic-Labs-AI/PACT-Pluginnpx agentmods add skills/synaptic-labs-ai/pact-plugin/pact-teachbackWrote 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/synaptic-labs-ai/pact-plugin/pact-teachback)<a href="https://agentmods.dev/skills/synaptic-labs-ai/pact-plugin/pact-teachback"><img src="https://agentmods.dev/badge/skills/synaptic-labs-ai/pact-plugin/pact-teachback.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00044 | $0.04523 |
| Opus 5 | $0.00022 | $0.02261 |
| Sonnet 5 | $0.00009 | $0.00905 |
| Haiku 4.5 | $0.00004 | $0.00452 |
Grade A, and why
pact-teachback 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 3d 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 — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Teachback — Store Now
Canonical schema at a glance
The full teachback payload — all required fields plus the optional method-reconstruction sub-object — at the correct nesting level. Skim this first if you only have time for one section; the rest of the skill explains the why and the surrounding choreography.
TaskUpdate(taskId, metadata={
# Top-level metadata key #1: teachback_submit
# 5 canonical fields. variety_acknowledgment is an OBJECT (not a string).
# reasoning_reconstruction is a sibling field of the other 4 (not nested
# inside any of them, not placed on metadata.handoff).
"teachback_submit": {
"understanding": "<...>",
"most_likely_wrong": "<...>",
"least_confident_item": "<...>",
"first_action": "<...>",
"variety_acknowledgment": {
"rationale_articulates_this_dispatch": "yes" | "no" | "concern",
"concern": "<required when value != 'yes'>"
},
# Sibling field — optional below variety 11, required at 11+.
# The 3 sub-keys are EXACTLY these three names, no substitutions.
"reasoning_reconstruction": {
"decision_attribution": "<...>",
"assumption_trace": "<...>",
"contingency_clause": "<...>"
}
},
# Top-level metadata key #2: intentional_wait
# SEPARATE top-level sibling of teachback_submit — NOT nested inside it.
# Written via a SECOND TaskUpdate call after the notify SendMessage; see
# Action: store teachback now below for the load-bearing 3-step ordering.
"intentional_wait": {
"reason": "awaiting_lead_completion",
"expected_resolver": "lead",
"since": "<canonical_since() output>"
}
})
Each field's full purpose, the variety-band trigger for reasoning_reconstruction, and the 4 common wrong-shape mistakes appear in the sections below. The Common mistakes section enumerates the 4 wrong shapes the runtime advisory layer at hooks/task_lifecycle_gate.py catches at write time.
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.
- 3d ago Changed f458a608adaf
- 8d ago First seen · 219 lines · 44 tokens per session scan A 33c79dca5d07
pact-teachback is a skill published in the GitHub repository Synaptic-Labs-AI/PACT-Plugin (71 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 4,523 once invoked, about $0.0002 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 2026-08-30.
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