aegis

aegis is a skill for Claude Code, Codex from IamK77/Skill. It costs 228 tokens per session (4,166 once invoked), scanned A, original, Apache-2.0.

A security-by-design process that considers protection throughout software development and operation. It covers threat modeling, secure design, input validation, access controls, automated security checks, common web risks, and operations.

In plain words
What is it for?
Use it when designing, coding, reviewing, testing, or operating a system. It helps identify threats, limit access, handle untrusted input, and add security checks to development and delivery.
Why use it?
Adding security only at the end can leave weaknesses in the system's basic design, where fixing them may require rebuilding parts of it. Treating security as a continuous concern brings risks into decisions and checks earlier.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/iamk77/skill/aegis
Any agent
npx skills add IamK77/Skill --skill aegis
Clone the repo
git clone --depth 1 https://github.com/IamK77/Skill

Made for: Claude Code, Codex.

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 aegis

README.md
[![agentmods](https://agentmods.dev/badge/skills/iamk77/skill/aegis.svg)](https://agentmods.dev/skills/iamk77/skill/aegis)
Your own site
<a href="https://agentmods.dev/skills/iamk77/skill/aegis"><img src="https://agentmods.dev/badge/skills/iamk77/skill/aegis.svg" alt="Measured on agentmods" height="20"></a>
Per session 228 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,166 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00228 $0.04166
Opus 5 $0.00114 $0.02083
Sonnet 5 $0.00046 $0.00833
Haiku 4.5 $0.00023 $0.00417

Measured 3d ago against content hash d394710bb3a7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

aegis 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.

skills/engineering/aegis/SKILL.md · 165 lines

How it starts

The opening of the file, as written. The whole thing — 165 lines — stays where its author put it; the contents beside it link to each section on GitHub.

aegis

!checklist init ${CLAUDE_SKILL_DIR} --force

Security is not the last check before launch; it is a line that runs through every part of the lifecycle. Treating it as something you add once the features work — bolt-on security — fails almost by construction, because the most damaging weaknesses live in architecture and design, where they cannot be patched in afterward, only rebuilt. The correct posture is the one this whole suite keeps returning to: shift security left (the DevSecOps idea), the same "catch it early, surface it cheap" instinct as quality-left and red-means-stop. This skill is the shield — the discipline of building a system secure-by-design — across six gated stages, and it will not advance past a GATE until the checklist tool clears it. Its adversarial counterpart, the spear that attacks what this builds to prove it holds, is the gungnir skill.

Security is where the agent era is most dangerous, because a vulnerability is the worst possible fit for how an agent works:

  • The agent writes insecure code by default. Its training distribution is full of vulnerable patterns — string-concatenated SQL, eval, weak or homemade crypto, hard-coded keys — and it reproduces them, because insecure code works perfectly until someone attacks it.
  • A vulnerability passes every green test. It is the absence of an attack so far, not a failure — so it sails through every functional test and every green dashboard, and a green-optimizing agent ships it believing the job is done. Security is the ultimate "green ≠ correct."
  • The agent has no threat model and trusts its input. It does not spontaneously ask "who would attack this, and how"; it writes the happy path and treats input as friendly, which is injection and XSS.
  • The agent invents crypto/auth and over-grants to make it work. It will happily generate a custom authentication scheme or widen a permission to *:* to clear an error, feeling none of the risk.

So the rule that governs this skill: security must be woven in and enforced at every stage, never trusted to instinct — because the most prolific contributor is an agent whose every default is the insecure one, and whose green light certifies nothing about whether the system can be attacked. The aim is not absolute security (which is impossible and infinitely costly) but risk management: identify what is most worth protecting and most likely to be attacked, and concentrate the defense there.

Discipline: finish every GATE before the next stage. GATEs are hard — never skip, batch past, or self-certify a stage you have not done. The checklist tool enforces the order; let it. Commands address stages by name.

Read references/agent-era-shifts.md first — it is the heart: what each security practice becomes once the code is written by something with no threat model, no felt risk, and a relentless pull toward whatever turns the light green. If $ARGUMENTS is a throwaway with no sensitive data and no exposure, this machinery is overkill — say so. The leanest sufficient defense for the system's real risk is the goal, not maximum ceremony.

Speak the user's language, or the risk gets accepted blind. This skill makes the user own real trade-offs only they can price: what data is sensitive, what an outage or breach costs, which compliance regime applies, how much defense a risk earns. Read their fluency and gloss a term on first use (threat model, STRIDE, least privilege, defense in depth, SAST/DAST/SCA, CIA, zero trust). A user who signs off on "this residual risk is acceptable" in words they never parsed has not accepted it — and the FRAME, MODEL, and OPERATE judgments this skill leans on them for are then hollow.

Read the full file on GitHub · 165 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. 3d ago First seen · 165 lines · 228 tokens per session scan A d394710bb3a7

Subscribe to this mod's changes

aegis is a skill published in the GitHub repository IamK77/Skill (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 228 tokens to every session and 4,166 once invoked, about $0.0011 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.

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