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.
git clone --depth 1 https://github.com/FlyFission/nuclear-grade-context-engineeringWrote 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/flyfission/nuclear-grade-context-engineering/ng-trace)<a href="https://agentmods.dev/commands/flyfission/nuclear-grade-context-engineering/ng-trace"><img src="https://agentmods.dev/badge/commands/flyfission/nuclear-grade-context-engineering/ng-trace/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/commands/flyfission/nuclear-grade-context-engineering/ng-trace"><img src="https://agentmods.dev/badge/commands/flyfission/nuclear-grade-context-engineering/ng-trace.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 | $0.00000 | $0.00796 |
| Opus 5.5 | $0.00000 | $0.00318 |
| Sonnet 5.5 | $0.00000 | $0.00159 |
| Haiku 4.5 | $0.00000 | $0.00080 |
Grade A, and why
ng-trace 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.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ng-trace
Portable command prompt generated from skills/recording-what-an-agent-did/SKILL.md. Edit the skill, then run python tools/ng.py gen-commands; do not edit this file by hand.
Captures an agent run's tool calls, decision points, inputs, outputs, token use, and approval steps as a clear, repeatable record linked into the packet trace and verification record. Use when how the agent got there matters for debugging, auditing, cost review, or defending a release decision. Do not use for a read-only run that changes nothing, or to produce a certified compliance audit trail.
Use when
- An agent ran tool calls that matter (file writes, API calls, command runs) and the packet needs evidence you can check.
- A release decision turns on whether the agent followed the plan, the scope, and its power limits.
- Token use, delay (latency), or cost is one of the things you have to verify for this change.
- A reviewer or auditor needs to rebuild what the agent did without reading a raw chat log.
- A review after an incident, or an OPEX review (a lessons-from-operation review), needs repeatable evidence of how the agent behaved.
Do not use when
- The run was read-only exploring, with no real side effects and nothing riding on a release.
- The packet mode is Quick and the proof is one simple step that always gives the same answer.
- A full tracing platform already captures and exports this run data. Link to its output instead of copying it.
Inputs
- The agent's run log, chat transcript, tool-call records, or trace export.
basis.md(the scope the run was meant to stay in, the allowed actions, and the stop conditions).plan.md(the planned order of steps).- Token use, delay, and cost data where they matter.
- Records of human approval steps.
Prompt text
Trace this agent run and produce clear evidence.
Inputs:
- packet: .nuclear/changes/<slug>/
- execution source: <log / transcript / tool-call export>
- authority scope: <basis.md section or inline>
- token/latency data available: <yes/no>
- approval gates exercised: <list or none>
For each consequential step (tool call, file edit, command run, API call,
approval gate):
- Name the action and the tool.
- Record the inputs (shortened) and the output or result.
- Set an evidence status: pass, gap, fail, or not applicable.
- At decision points: record the choice made, the limit applied, and the authority check.
- For approval gates: the reviewer, the date, and the decision.
Return:
- trace rows for trace.md: step, action, inputs, outputs, evidence status.
- the decision-point records.
- a summary of token use and speed (if available).
- a run summary: steps within scope, steps uncertain, and gaps.
- a link from each trace row to the claim in verification.md it supports.
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 · 68 lines · 0 tokens per session scan A 80fb77adcdd4
ng-trace is a command published in the GitHub repository FlyFission/nuclear-grade-context-engineering (33 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 796 tokens. 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.
Other commands, from other repositories
coder-eval-implement-plan
Implement an approved codereval plan phase by phase with risk-scaled per-phase review, then a final code review.
capture-feedback
Quick feedback capture with structured signals.
check-gates
Run a Pre-Action Gate check against prevention rules before executing a risky action.
task-verify
PitWay: Run an inprogress task's approved verification command and persist evidence.
milestone-list
PitWay: List every milestone with a concise one-line status.
bet
Lock a shaped Shape-Up pitch as a bet for the next cycle.