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 pproenca/dot-skills --skill adversarial-tanstackgit clone --depth 1 https://github.com/pproenca/dot-skillsWrote 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/pproenca/dot-skills/adversarial-tanstack)<a href="https://agentmods.dev/skills/pproenca/dot-skills/adversarial-tanstack"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/adversarial-tanstack/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/pproenca/dot-skills/adversarial-tanstack"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/adversarial-tanstack.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00143 | $0.01326 |
| Opus 5 | $0.00072 | $0.00663 |
| Sonnet 5 | $0.00029 | $0.00265 |
| Haiku 4.5 | $0.00014 | $0.00133 |
Grade A, and why
adversarial-tanstack 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 5d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adversarial TanStack Gate
A merge gate for TanStack Start + TypeScript web-app changes — a pass/fail gate: a single blind reviewer subagent judges the work against this gate's rules with an adversarial mandate, and the work passes only when every rule is PASS or N/A. This skill renders verdicts; it never fixes the work.
Rules are pinned to @tanstack/react-start 1.168+ (v1 RC, July 2026) and TypeScript 5.8–6.x semantics.
When to Apply
- A TanStack Start feature, route, or server function is about to merge and needs an objective PASS/FAIL, not advisory feedback.
- An agent (Claude, Codex) authored Start app code and you want an independent check its author bias cannot rubber-stamp.
- A diff touches the client/server boundary — env vars, loaders, server functions, auth — where a wrong PASS ships secrets or unauthorized data access.
- Auditing an existing Start codebase file set against the current v1 RC API surface (stale
.inputValidator(), removedcreateServerFileRoute).
Do not apply to non-Start React apps (most serverfn/boundary/ssr rules will return N/A and the gate degenerates to a TypeScript check) or when the user wants explanations and refactors rather than a verdict.
Review Protocol
Follow these steps exactly — the gate's value is that every review runs the same way.
- Identify the target. Pin down exactly what is under review (a diff, a set of files, a PR) and note the ref/paths so the review runs against an unambiguous, fixed target. Always include
tsconfig.json,src/router.tsx, andsrc/start.ts(if present) in the target paths — several rules are decided by those files even when the diff does not touch them. - Load the rules. Read references/_sections.md and every rule file in
references/(allboundary-*.md,serverfn-*.md,sec-*.md,ssr-*.md,types-*.md,tscfg-*.mdfiles). - Compose the reviewer prompt. Fill references/reviewer-prompt.md with the rules and the target. The composed prompt must be fully self-contained — a reviewer sees no conversation history, so nothing may refer to context outside the prompt.
- Dispatch one blind reviewer. Launch a single Task subagent whose entire input is the composed prompt — no conversation context, no commentary alongside it.
- Render fail-closed. The reviewer's structured output is the verdict — there is no merge step. Overall verdict is PASS only when every rule is PASS or N/A; any single FAIL fails the gate. Never average, weigh severity, or waive a rule — a "minor" FAIL is a FAIL.
- Render the verdict. Fill assets/templates/verdict.md. On FAIL, aggregate the reviewer's "missing for PASS" suggestions into the fix list, each with its location, ordered by category importance. Every rule whose final result is FAIL must appear in the fix list with a change concrete enough to apply as written — if the reviewer's suggestion only restates the violation, derive the fix from the rule's Correct example before rendering.
What ships with it
27 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.
- assets/templates/verdict.md 1.4 KB
- gotchas.md 2.3 KB
- metadata.json 1.5 KB
- references/_sections.md 1.7 KB
- references/boundary-client-env-prefix.md 1.3 KB
- references/boundary-env-server-context.md 1.9 KB
- references/boundary-loader-no-secrets.md 1.4 KB
- references/reviewer-prompt.md 3.2 KB
- references/sec-auth-at-handler.md 1.6 KB
- references/sec-csrf-with-custom-start.md 1.2 KB
- references/sec-no-account-enumeration.md 1.7 KB
- references/sec-private-cache-control.md 1.5 KB
- references/sec-session-cookie-flags.md 1005 B
- references/serverfn-current-api.md 1.6 KB
- references/serverfn-post-mutations.md 1.4 KB
- references/serverfn-static-imports.md 1.1 KB
- references/serverfn-validate-input.md 1.5 KB
- references/ssr-deterministic-render.md 1.5 KB
- references/ssr-per-request-instances.md 1.6 KB
- references/ssr-suspense-for-loader-data.md 1.4 KB
- references/tscfg-erasable-syntax.md 1.5 KB
- references/tscfg-no-verbatim-module-syntax.md 1.1 KB
- references/tscfg-strict-baseline.md 1.1 KB
- references/types-exhaustive-switch.md 1.6 KB
- references/types-justified-nonnull.md 1.4 KB
- references/types-no-escape-hatches.md 1.6 KB
- references/types-parse-external-data.md 1.6 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.
- 5d ago First seen · 57 lines · 143 tokens per session scan A b083dce57430
adversarial-tanstack is a skill published in the GitHub repository pproenca/dot-skills (205 stars, last pushed 24d ago), licensed MIT. It adds 143 tokens to every session and 1,326 once invoked, about $0.0007 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 2026-09-03.
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