recording-what-an-agent-did

recording-what-an-agent-did is a skill for Claude Code from FlyFission/nuclear-grade-context-engineering. It costs 90 tokens per session (1,720 once invoked), scanned A, original, MIT.

A written record of an AI agent's important actions, decisions, inputs, outputs, approvals, and resource use during a run.

In plain words
What is it for?
Use it to create step-by-step evidence in trace and verification records, linked to the final release decision.
Why use it?
It shows how the result was produced, which helps investigate problems, review costs, check permissions, and support a release decision.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Claude Code.

Part of the nuclear-grade plugin — 29 skills, 28 commands, 5 agents shipped together

Good fit Use it to create step-by-step evidence in trace and verification records, linked to the final release decision.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/flyfission/nuclear-grade-context-engineering/recording-what-an-agent-did
Install

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.

Any agent
npx skills add FlyFission/nuclear-grade-context-engineering --skill recording-what-an-agent-did
Clone the repo
git clone --depth 1 https://github.com/FlyFission/nuclear-grade-context-engineering

Made for: Claude Code.

Or install nuclear-grade, the plugin that ships this one along with the rest of its 29 skills, 28 commands, 5 agents.

Wrote 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.

agentmods badge for recording-what-an-agent-did

README.md
[![agentmods](https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/recording-what-an-agent-did/github.svg)](https://agentmods.dev/skills/flyfission/nuclear-grade-context-engineering/recording-what-an-agent-did)
Your own site
<a href="https://agentmods.dev/skills/flyfission/nuclear-grade-context-engineering/recording-what-an-agent-did"><img src="https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/recording-what-an-agent-did/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.

agentmods 80×15 button for recording-what-an-agent-did

Your own site · 80×15
<a href="https://agentmods.dev/skills/flyfission/nuclear-grade-context-engineering/recording-what-an-agent-did"><img src="https://agentmods.dev/badge/skills/flyfission/nuclear-grade-context-engineering/recording-what-an-agent-did.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,720 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00090 $0.01720
Opus 5 $0.00045 $0.00860
Sonnet 5 $0.00018 $0.00344
Haiku 4.5 $0.00009 $0.00172

Measured 11d ago against content hash b5497c783e22, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

recording-what-an-agent-did 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 11d 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.

skills/recording-what-an-agent-did/SKILL.md · 124 lines

How it starts

The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Recording What an Agent Did

Overview

A "does it work" check proves what an agent produced, not how it got there. Sometimes how it got there matters: for debugging, for auditing, for reviewing cost, or for defending a release decision. This skill says what to record about the run, how much detail to capture, and how to link it into the packet's trace.md and verification.md as evidence someone else could reproduce.

Decision contract

  • Claim checked: every step that mattered -- tool call, edit, command, API call, approval -- has a recorded result and status, and each stayed inside the power basis.md granted.
  • Artifact observed: the run log/transcript/trace export against basis.md and plan.md -> step-level trace rows, decision-point and approval records, and a token/delay summary in trace.md/verification.md, linked to ship.md.
  • Decision affected: warn -- the step-level execution evidence the ship.md decision relies on.
  • Failure class: unevidenced-run (a stayed-in-scope claim with no step-level evidence, or unexplained cost).
  • Next action: record the gap for ship.md; a power breach or unexpected side effect escalates to pause/incident.

When to Use

  • 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.

When Not to Use

  • 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.

Read the full file on GitHub · 124 lines

Changes

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.

  1. 11d ago First seen · 124 lines · 90 tokens per session scan A b5497c783e22

Subscribe to this mod's changes

recording-what-an-agent-did is a skill published in the GitHub repository FlyFission/nuclear-grade-context-engineering (33 stars, last pushed yesterday), licensed MIT. It adds 90 tokens to every session and 1,720 once invoked, about $0.0005 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.