nuclear-grade-context-engineering
AGENTS.md33 starsChanged 16 days agoMITView on GitHub
AI agents working in this repo should treat Nuclear-grade as a way to gather evidence, not a brand to show off. The idea is simple. Keep a questioning attitude. Use small habits from Human Performance Improvement (HPI). And keep the approved version under control for AI-assisted software work. In practice that means: question assumptions, write down what the change must do, brief the work, double-check risky actions, and hand off cleanly. Keep the controlled files, the evidence, the decisions, the…
Where files are headingNew AGENTS.md files have more rules about keeping secrets out of the code, and fewer about code style.
Of the AGENTS.md files we read, the 31,700 first seen in the last six months, against the older ones: the kind of rule that gained most share, and the kind that lost most. About files like this in general, not this one, and an estimate, since a kind is a pattern in the words.
In this repository34 other files it gives its agents.
- challenge/AGENTS.mdAGENTS.md
- challenge/CLAUDE.mdCLAUDE.md
- CLAUDE.mdCLAUDE.md
- breaking-down-the-workSkill
- briefing-an-agentSkill
- checking-factsSkill
- checking-legal-and-safety-wordingSkill
- checking-release-readinessSkill
- checking-source-claimsSkill
- checking-what-a-change-affectsSkill
- choosing-what-to-controlSkill
- closing-stale-packetsSkill
- creating-change-recordsSkill
- deciding-who-decidesSkill
- declaring-intentSkill
- double-checking-before-actingSkill
- handing-off-workSkill
- learning-from-experienceSkill
- organizing-project-foldersSkill
- proving-claimsSkill
- questioning-attitudeSkill
- rating-change-riskSkill
- recording-a-known-good-versionSkill
- recording-what-an-agent-didSkill
- reporting-shared-defectsSkill
- responding-to-incidentsSkill
- reviewing-code-qualitySkill
- running-a-review-panelSkill
- staying-on-missionSkill
- stress-testing-agent-changesSkill
- tracking-deficienciesSkill
- using-nuclear-gradeSkill
- verifying-final-artifactsSkill
- vetting-outside-code-and-modelsSkill
The file
We split this AGENTS.md into the rules it gives an agent
11 rules. About 0 are common, 9 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈9
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- could be automatic: a setting could enforce it
- Very specific: line 8
Start with this file and the right change record.
- Distinctive: line 9
Treat instruction conflicts as blockers, not judgment calls: name the conflicting sources, apply the host's documented precedence, and stop …
- Distinctive: line 15
Use lessons from real operation (OPEX) when a near miss, a bad handoff, a review surprise, or an operating signal should update a lasting …
- Distinctive: line 20
Prefer links and short status labels over long, repeated text.
- Distinctive: line 21
Run the right tests and checker commands before you say the work is done.
- Very specific: line 25
Do not invent a new proof path for routine edits.
- Distinctive: line 33
If you skip a full pre-PR run, say why the narrower proof still covers the files you changed.
- Distinctive: line 41
add compliance or assurance claims.
- Distinctive: line 44
treat their own confidence or a fluent intent statement as evidence, or rubber-stamp another agent's output as an independent check.
- Distinctive: line 53
Every completion report names:
- Distinctive: line 60
Add triggered details only when they apply: handoff, self-check, OPEX, or trust records when used or required.
≈ “Common” is an estimate: at least 1 in 5 of the 40,246 AGENTS.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent Guidance
AI agents working in this repo should treat Nuclear-grade as a way to gather evidence, not a brand to show off. The idea is simple. Keep a questioning attitude. Use small habits from Human Performance Improvement (HPI). And keep the approved version under control for AI-assisted software work. In practice that means: question assumptions, write down what the change must do, brief the work, double-check risky actions, and hand off cleanly. Keep the controlled files, the evidence, the decisions, the version everyone agreed is correct, and the release stance all linked together.
Default behavior
- Start with this file and the right change record. Follow links into
README.mdorWORKFLOWS.mdonly when the task needs them; do not preload either wholesale. - Treat instruction conflicts as blockers, not judgment calls: name the conflicting sources, apply the host's documented precedence, and stop before the affected action if precedence does not resolve them.
- Use the lightest mode that is still honest. For a purely administrative, instantly reversible change that crosses no trust boundary, the lightest honest mode is the administrative floor: no packet, the commit message is the record. Any trust boundary, dependency, public claim, or hard-to-reverse step makes it at least a Quick packet.
- Tie every claim to evidence.
- Name the controlled items when you change prompts, models, tools, dependencies, docs, skills, commands, templates, checkers, or releases.
- Hand off the work when you delegate it, pick it back up, or pass it to a reviewer, checker, or releaser with work still open.
- Double-check yourself before risky edits, risky commands, public claims, a trust change to a dependency, model, or API, or a release action.
- Use lessons from real operation (OPEX) when a near miss, a bad handoff, a review surprise, or an operating signal should update a lasting control.
- Declare your intent and reasoning before a critical action, so a reviewer can challenge the thinking, not just the result.
- Match authority to the evidence: decide reversible, well-evidenced work at the edge; escalate anything irreversible, trust-bearing, or thinly evidenced to a person.
- Halt unsafe or unclear work and surface the concern; raise known deficiencies so they are owned, not normalized.
- Hand off so the next owner is more capable, not more dependent.
- Prefer links and short status labels over long, repeated text.
- Run the right tests and checker commands before you say the work is done.
Verification routing
Do not invent a new proof path for routine edits. Use the pre-PR commands in
CONTRIBUTING.md, then narrow only when the change is clearly
smaller than a full run:
- docs-only wording:
git diff --checkplus the nearest public-doc or token test; - template, skill, command, or checker behavior: the targeted pytest file plus
python tools/ng.py doctor .; - worked-example evidence: re-run the example validator or example test named in the change record.
If you skip a full pre-PR run, say why the narrower proof still covers the files you changed.
Authority boundaries
Agents must not assume they may:
- change the release stance without a ship-readiness record;
- make bigger claims about where the ideas come from;
- add compliance or assurance claims;
- edit security-sensitive, credential, network, or production-facing material without clear permission;
- invoke "authority to information" to skip a required human gate on an irreversible or trust-bearing action;
- treat their own confidence or a fluent intent statement as evidence, or rubber-stamp another agent's output as an independent check;
- overwrite change records or templates without saying so.
Skill loading rule
Load skills by trigger, not by inventory. First screen the work for risk, evidence, decision-rights, public-claim, trust-boundary, handoff, release, incident, or hard-to-reverse triggers. Then load the smallest skill set that can change the action, evidence, gate, decision right, claim wording, or handoff. Use the decision matrix in CORE.md to route the trigger; treat SKILLS.md as a discovery catalog, not a preload list. If a trigger is present or ambiguous, load the matching skill or state the specific evidence showing why it is not needed. Confidence is not evidence.
Completion standard
Every completion report names:
- the files it changed;
- the change record or reasoning it used;
- the evidence it ran;
- the gaps still open.
Add triggered details only when they apply: handoff, self-check, OPEX, or trust records when
used or required; intent and decision rights for critical actions; and boundary wording for
public claims. Do not pad routine completions with not applicable declarations.
Boundary note
Agent work in this repo does not create formal verification and validation, compliance, certification, safety, security, regulatory adequacy, or legal advice. None of those.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

