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/lookoutnpx skills add IamK77/Skill --skill lookoutgit clone --depth 1 https://github.com/IamK77/SkillWrote 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/skills/iamk77/skill/lookout)<a href="https://agentmods.dev/skills/iamk77/skill/lookout"><img src="https://agentmods.dev/badge/skills/iamk77/skill/lookout.svg" alt="Measured on agentmods" 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 | $0.00216 | $0.03720 |
| Opus 5 | $0.00108 | $0.01860 |
| Sonnet 5 | $0.00043 | $0.00744 |
| Haiku 4.5 | $0.00022 | $0.00372 |
Grade A, and why
lookout 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.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
lookout
!checklist init ${CLAUDE_SKILL_DIR} --force
A lookout watches the real horizon — the live sea, not the chart — and is also the conscience posted to call danger before the ship runs into it. lookout is the sixth skill of the surface suite, the delivery-and-observability lens, and it carries the suite's ethics across the line from philosophy into a launch gate. Its mindset is one shift: shipping is not the finish line, it is the start of the conversation with reality. Its product is a delivery-and-observability setup — preview per PR, RUM and error tracking, an analytics-and-experiment framework — plus the pre-launch ethics gate that the objective function from bearings must pass. It runs across gated stages and will not advance past a GATE until the checklist tool clears it — order enforced, substance yours.
The heavy part, stated up front: the moment the metrics dashboard exists, it starts pulling every decision — so the ethics must already be in place. A/B testing is, mathematically, a gradient-descent optimizer: each experiment keeps the higher-scoring variant, and run thousands of times it slides down the gradient of whatever metric you chose. Point that optimizer at an engagement metric — time-on-site, scroll depth — over a human nervous system, and it will discover manipulation as a local optimum: infinite scroll, variable-ratio rewards, removed stopping cues, all selected because they move the number, with no person ever sitting down to design a dark pattern. This is Goodhart's law on a human, the same shape as AI misalignment: optimize a proxy hard enough and you get the proxy, not the intent. The real villain is the loss function — which is why the objective-function charter is set in bearings, before the dashboard exists, and audited here, before any metric-driven launch.
This is where the agent era bites:
- The agent treats launch as the end. It ships, the task turns green, and it never wires the feedback loop — no preview to judge perception by eye, no RUM, no error tracking — so the team flies blind exactly where the spec lives (the real user's nervous system).
- The agent instruments by lab, not field, and tracks vanity. It will trust a fast-machine/fast-network lab number, miss the mid-range-phone-on-4G truth, and happily collect every event "for analytics" — monitoring debt and a privacy liability with no decision attached.
- The agent will optimize whatever metric it's handed, including engagement. It feels nothing about the reflective-vs-impulsive-self betrayal, so left alone it points the optimizer at the number that grows, and the optimizer finds the manipulation. The conscience is not a thing the agent supplies — it must be a gate.
Read references/the-membrane.md first — the heart; for lookout, the ethics axis is the spine (friction as the moral primitive, manipulation as bypassing agency, the impulsive-vs-reflective self, A/B as a gradient toward exploitation) along with the mind axis (RUM = psychophysics as numbers). Load at the start, re-check at every gate.
Speak the user's language. Almost every call here is the user's — which metric is the north-star, is this experiment honest, is this default serving the user. Read their fluency and gloss a term on first use (preview deploy, feature flag / progressive rollout, RUM vs lab, Core Web Vitals (LCP/INP/CLS), a guardrail metric, the gradient-descent framing of A/B, the reflective vs impulsive self, friction symmetry / GDPR Art. 7). A metric decision the user can't weigh is an ethics imposed, not shared.
What ships with it
8 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.
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.
- 3d ago First seen · 135 lines · 216 tokens per session scan A 8120557b2156
lookout is a skill published in the GitHub repository IamK77/Skill (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 216 tokens to every session and 3,720 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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