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 skills add LucasSantana-Dev/sharekit --skill app-teardowngit clone --depth 1 https://github.com/LucasSantana-Dev/sharekitWrote 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/lucassantana-dev/sharekit/app-teardown)<a href="https://agentmods.dev/skills/lucassantana-dev/sharekit/app-teardown"><img src="https://agentmods.dev/badge/skills/lucassantana-dev/sharekit/app-teardown/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.
<a href="https://agentmods.dev/skills/lucassantana-dev/sharekit/app-teardown"><img src="https://agentmods.dev/badge/skills/lucassantana-dev/sharekit/app-teardown.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00152 | $0.01177 |
| Opus 5.5 | $0.00061 | $0.00471 |
| Sonnet 5.5 | $0.00030 | $0.00235 |
| Haiku 4.5 | $0.00015 | $0.00118 |
Grade A, and why
app-teardown 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 1mo 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
App Teardown
Studies a live product the way a chef eats at a rival's restaurant: walk the real flows, name what works, explain WHY it works for them, and decide what transfers to our context. The output is a decision artifact, not a tour.
Use When
- A live app/product should be mined for ideas applicable to one of our projects.
- Before building a surface that a named competitor/product already does well.
- User names a product and asks what to learn, steal, or adapt from it.
Do Not Use When
- Target is a repo/codebase →
code-teardown. - Only visual direction is wanted (moodboard, type, palette) →
frontend-reference-hunt. - Understanding OUR OWN system's internals →
doc-and-modernize.
Inputs / Prereqs
- Target URL + whether login is needed (drive the user's Chrome via
claude-in-chrome). - OUR context lock: which project the ideas land in, its goals and constraints.
- Memory state-check FIRST:
reference_<target>_evaluated_*note exists → surface prior outcome and stop unless the revisit condition is met.
Workflow
- Scope + constraint capture — target, key flows to walk, and the gate question: why does their design work FOR THEM (scale, audience, pricing model, compliance, platform, legacy)? Record it; it powers the cargo-cult gate later.
- Live exploration (claude-in-chrome) — walk onboarding, core flow, settings, empty
states, error recovery, upgrade/paywall moments. Screenshot each finding into
<project>/.claude/design/refs/. Note deliberate ABSENCES and simplifications too. - Map by dimension — UX (interaction, feedback, empty/error states), Features (jobs-to-be-done, scope cuts, free-vs-paid line), Visual design (type, spacing, components, motion), Copy (tone, terminology), Growth (activation, referral, retention hooks). 2+ dimensions minimum; skip dimensions irrelevant to the brief.
- State-check per candidate finding — do WE already have it? Query graphify
(
graphify query) when the target project hasgraphify-out/, plus grep/memory. Mark hitsalready-haveinstead of re-proposing them. - Verdict + rationale per finding — apply the contract in
references/teardown-contract.md: evidence,
adopt | adapt | already-have | reject, the mandatory constraint rationale ("[their constraint] → [applies to us?] → [action]"), effort, landing spot in our repo. - Emit + remember — report to
<project>/docs/reference/<target>-teardown-<date>.md(committable). Memory notereference_<target>_evaluated_<date>.mdwith outcome + revisit condition; an "evaluated → nothing" outcome is a valid, valuable result (prevents re-evaluation — megabrain/llmwiki precedent). Summary line: "N findings, A adopt, D adapt, H already-have, R rejected".
What ships with it
1 file 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.
- 1mo ago First seen · 96 lines · 152 tokens per session scan A 7ce79e67725e
app-teardown is a skill published in the GitHub repository LucasSantana-Dev/sharekit (1 stars, last pushed 3d ago), licensed MIT. It adds 152 tokens to every session and 1,177 once invoked, about $0.0006 per session on Opus 5.5. 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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