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 code-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/code-teardown)<a href="https://agentmods.dev/skills/lucassantana-dev/sharekit/code-teardown"><img src="https://agentmods.dev/badge/skills/lucassantana-dev/sharekit/code-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/code-teardown"><img src="https://agentmods.dev/badge/skills/lucassantana-dev/sharekit/code-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 | $0.00168 | $0.01259 |
| Opus 5.5 | $0.00067 | $0.00504 |
| Sonnet 5.5 | $0.00034 | $0.00252 |
| Haiku 4.5 | $0.00017 | $0.00126 |
Grade A, and why
code-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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Teardown
Reads someone else's codebase to answer one question: what do they do that WE should do?
Same contract as app-teardown (live apps); this one targets repos and reads code.
Output is a decision artifact with verdicts, not an architecture tour — for "how does X
work" documentation use doc-and-modernize.
Use When
- An external repo should be mined for architecture/pattern/DX/tooling ideas for one of our projects.
- User names a repo, OSS project, or codebase and asks what to learn, adopt, or steal from it.
- Evaluating a trending project ("should we care about X?") — the negative outcome is captured too.
Do Not Use When
- Target is a live product to browse →
app-teardown. - You will contribute to or modify the target repo →
adt-repo-intake. - Documenting OUR OWN system →
doc-and-modernize.
Inputs / Prereqs
- Target repo (URL or local path). Clone shallow to
${DEV_ROOT}/<repo>(storage policy; never$HOME, never internal disk). - OUR context lock: which project the ideas land in, its stack and constraints.
- Memory state-check FIRST:
reference_<target>_evaluated_*exists → surface prior outcome and stop unless the revisit condition is met. - Target is read-only: no issues, no PRs, no edits there.
Workflow
- Scope + constraint capture — why does their design work FOR THEM (scale, team size, ecosystem, age, funding model)? Record upfront; feeds the cargo-cult gate.
- Shallow clone + intake sweep —
git clone --depth 1. Read README, docs/, ADRs, CONTRIBUTING, CI config, package manifest, top-level layout. For large repos dispatch read-onlyExploreagents per area instead of reading serially. - Map by dimension — Architecture (boundaries, data flow, state), Code patterns (idioms, error handling, abstractions worth naming), DX (scripts, codegen, local-dev loop), Tooling/CI (build, release, quality gates), Testing (strategy, fixtures, ratio), Docs conventions (ADRs, changelogs, onboarding). 2+ dimensions minimum; note deliberate ABSENCES (what they chose not to build).
- State-check per candidate finding — do WE already have it? graphify query on the
target project (if
graphify-out/exists) + grep + memory. Hits →already-have. - Verdict + rationale per finding — apply the shared contract:
~/.agents/skills/app-teardown/references/teardown-contract.md(evidence asfile:lineat a pinned commit SHA, verdict, mandatory "[their constraint] → [applies to us?] → [action]" rationale, effort, landing spot). - Emit + remember — report to
<project>/docs/reference/<target>-teardown-<date>.md. Memory notereference_<target>_evaluated_<date>.mdwith outcome + revisit condition; "evaluated → nothing" is a first-class outcome (megabrain/llmwiki precedent). Summary: "N findings, A adopt, D adapt, H already-have, R rejected". Remove the clone if nothing was adopted and no revisit is planned.
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 · 98 lines · 168 tokens per session scan A 65fa35b2336e
code-teardown is a skill published in the GitHub repository LucasSantana-Dev/sharekit (1 stars, last pushed 3d ago), licensed MIT. It adds 168 tokens to every session and 1,259 once invoked, about $0.0007 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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When delegating a task affected by this skill, include.
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Adversarial review of an increment before it ships, by a fresh context or another model family; every finding cites path:line and is re-verified. Use for "review", "qa", "critique this".
tech-debt-ci-review
Codex adapter for deep technical-debt and CI-stability audits. Use when asked to find test theater, flaky tests, missing or mis-scoped tests, brittle CI/toolchain behavior, structural debt blocking green PRs, or a remediation order for opencode-swarm.