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.
npx agentmods add skills/iamk77/skill/gungnirnpx skills add IamK77/Skill --skill gungnirgit clone --depth 1 https://github.com/IamK77/SkillWhat 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 | $0.00184 | $0.03910 |
| Opus 5 | $0.00092 | $0.01955 |
| Sonnet 5 | $0.00037 | $0.00782 |
| Haiku 4.5 | $0.00018 | $0.00391 |
Grade A, and why
gungnir 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 2d 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gungnir
!checklist init ${CLAUDE_SKILL_DIR} --force
The single most valuable security mindset is to think like an attacker and actively try to break your own system — because a defense is only ever proven by a real attack, never by a clean scan or a green test. This skill is the spear: authorized, adversarial penetration testing of a system to prove (or disprove) that the defenses the aegis skill built actually hold. It drives a real attack through its whole arc — scope, recon, scan, exploit, chain, report — across six gated stages, and it will not advance past a GATE until the checklist tool clears it.
The one hard boundary, gated first and never crossed: you attack only a system you own or have explicit, written authorization to test. Attacking anything else — a third-party service, a system you don't own, infrastructure outside the agreed scope — is out of bounds, full stop, regardless of intent. This skill is for authorized, defensive validation: your own staging environment, a system you've been contracted to test in writing, or a deliberately-vulnerable practice lab. STAGE 0 makes that authorization a hard gate, and it is the one gate that is never a judgment call.
Adversarial validation is where the agent era cuts both ways, and both edges matter:
- The agent can now actually run the attack —
nmap,sqlmap, an intercepting proxy — which makes continuous self-attack cheap and real. That capability is exactly why the authorization gate must be absolute: a tool that can find a hole can point at the wrong target, and the agent feels no instinct about whose system it is. - The agent shares the blind spots of whoever built the system. If the design, the code, and now the attack are all done by agents, they share a training distribution and an imagination — so an agent attacking a system it (or a sibling) built will miss the same things it missed building it. Agreement is not evidence. Real assurance needs independent angles, and on the highest-stakes systems, a genuinely independent (human) tester.
- The agent runs a scanner, sees an empty result, and declares "secure." A clean scan means known patterns weren't found — it is necessary and nowhere near sufficient. The creative work — chaining small flaws into a real exploit, abusing business logic no scanner understands — is exactly what the agent is weakest at and what this skill exists to force.
So the rule that governs this skill: a defense is proven only by a real, authorized attack — a clean scan is not proof — and you attack only what you are permitted to. The goal is not to "pass"; it is to find the holes while they are still cheap to fix.
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 adversarial testing becomes when the attacker is an agent that shares the defender's blind spots, can run the tools, and will mistake a clean scan for a secure system. If $ARGUMENTS is trivial and has nothing worth attacking, this machinery is overkill — say so.
Speak the user's language, and confirm the authorization out loud. This skill needs the user to set the scope, confirm ownership/authorization, and own the disposition of every finding. Read their fluency and gloss a term on first use (penetration test vs scan, recon, IDOR, injection, privilege escalation, scope, rules of engagement). A user who cannot confirm, plainly, that this target is theirs to attack has not authorized it — and STAGE 0 does not clear.
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .checklist.yml 5.4 KB
- LICENSE 11 KB
- NOTICE 649 B
- references/agent-era-shifts.md 27 KB
- references/chaining-and-impact.md 21 KB
- references/decision-tree.md 11 KB
- references/exploitation-by-class.md 30 KB
- references/recon-and-enumeration.md 20 KB
- references/report-fix-retest.md 27 KB
- references/scope-and-authorization.md 16 KB
- references/tools-and-practice.md 23 KB
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.
- 2d ago First seen · 158 lines · 184 tokens per session scan A 2cfe24e1980c
gungnir is a skill published in the GitHub repository IamK77/Skill (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 184 tokens to every session and 3,910 once invoked, about $0.0009 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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